System and method for video coding

ABSTRACT

An image encoder or decoder includes circuitry and a memory coupled to the circuitry. The circuitry, in operation, predicts a first set of samples for a first partition of a current picture with one or more motion vectors including a first motion vector and predicts a second set of samples for a first portion of the first partition with one or more motion vectors from a second partition different from the first partition. The samples of the first set of samples of the first portion of the first partition and of the second set of samples of the first portion of the first partition are weighted. A motion vector for the first portion of the first partition is stored which is based on one or both of the first motion vector and the second motion vector. The first partition is encoded or decoded using at least the weighted samples of the first portion of the first partition.

BACKGROUND Technical Field

This disclosure relates to video coding, and particularly to videoencoding and decoding systems, components, and methods for performing aninter prediction function to build a prediction of a current frame basedon a reference frame.

Description of the Related Art

With advancement in video coding technology, from H.261 and MPEG-1 toH.264/AVC (Advanced Video Coding), MPEG-LA, H.265/HEVC (High EfficiencyVideo Coding) and H.266/VVC (Versatile Video Codec), there remains aconstant need to provide improvements and optimizations to the videocoding technology to process an ever-increasing amount of digital videodata in various applications. This disclosure relates to furtheradvancements, improvements and optimizations in video coding,particularly in an inter prediction function to build a prediction of acurrent frame based on a reference frame.

BRIEF SUMMARY

In one aspect, an image encoder includes circuitry and a memory coupledto the circuitry. The circuitry, in operation, predicts a first set ofsamples for a first partition of a current picture with one or moremotion vectors including a first motion vector and predicts a second setof samples for a first portion of the first partition with one or moremotion vectors from a second partition different from the firstpartition. The samples of the first set of samples of the first portionof the first partition and of the second set of samples of the firstportion of the first partition are weighted. A motion vector for thefirst portion of the first partition is stored which is based on one orboth of the first motion vector and the second motion vector. The firstpartition is encoded using at least the weighted samples of the firstportion of the first partition.

In one aspect, an image encoder comprises a splitter which, inoperation, receives and splits an original picture into blocks, a firstadder which, in operation, receives the blocks from the splitter andpredictions from a prediction controller, and subtracts each predictionfrom its corresponding block to output a residual, a transformer which,in operation, performs a transform on the residuals outputted from theadder to output transform coefficients, a quantizer which, in operation,quantizes the transform coefficients to generate quantized transformcoefficients, an entropy encoder which, in operation, encodes thequantized transform coefficients to generate a bitstream, an inversequantizer and transformer which, in operation, inverse quantizes thequantized transform coefficients to obtain the transform coefficientsand inverse transforms the transform coefficients to obtain theresiduals, a second adder which, in operation, adds the residualsoutputted from the inverse quantizer and transformer and the predictionsoutputted from the prediction controller to reconstruct the blocks, andthe prediction controller coupled to an inter predictor, an intrapredictor, and a memory. The inter predictor, in operation, generates aprediction of a current block based on a reference block in an encodedreference picture. The intra predictor, in operation, generates aprediction of a current block based on an encoded reference block in acurrent picture. The inter predictor, in operation, predicts a first setof samples for a first partition of a current picture with one or moremotion vectors including a first motion vector and predicts a second setof samples for a first portion of the first partition with one or moremotion vectors from a second partition different from the firstpartition. The samples of the first set of samples of the first portionof the first partition and of the second set of samples of the firstportion of the first partition are weighted. A motion vector for thefirst portion of the first partition is stored which is based on one orboth of the first motion vector and the second motion vector. The firstpartition is encoded using at least the weighted samples of the firstportion of the first partition.

In one aspect, an encoding method comprises predicting a first set ofsamples for a first partition of a current picture with one or moremotion vectors including a first motion vector and predicting a secondset of samples for a first portion of the first partition with one ormore motion vectors from a second partition different from the firstpartition. The samples of the first set of samples of the first portionof the first partition and of the second set of samples of the firstportion of the first partition are weighted. A motion vector for thefirst portion of the first partition is stored which is based on one orboth of the first motion vector and the second motion vector. The firstpartition is encoded using at least the weighted samples of the firstportion of the first partition.

In one aspect, an image decoder includes circuitry and a memory coupledto the circuitry. The circuitry, in operation, predicts a first set ofsamples for a first partition of a current picture with one or moremotion vectors including a first motion vector and predicts a second setof samples for a first portion of the first partition with one or moremotion vectors from a second partition different from the firstpartition. The samples of the first set of samples of the first portionof the first partition and of the second set of samples of the firstportion of the first partition are weighted. A motion vector for thefirst portion of the first partition is stored which is based on one orboth of the first motion vector and the second motion vector. The firstpartition is decoded using at least the weighted samples of the firstportion of the first partition.

In one aspect, an image decoder comprises an entropy decoder which, inoperation, receives and decodes an encoded bitstream to obtain quantizedtransform coefficients, an inverse quantizer and transformer which, inoperation, inverse quantizes the quantized transform coefficients toobtain transform coefficients and inverse transform the transformcoefficients to obtain residuals, an adder which, in operation, adds theresiduals outputted from the inverse quantizer and transformer andpredictions outputted from a prediction controller to reconstructblocks, and the prediction controller coupled to an inter predictor, anintra predictor, and a memory. The inter predictor, in operation,generates a prediction of a current block based on a reference block ina decoded reference picture. The intra predictor, in operation,generates a prediction of a current block based on an encoded referenceblock in a current picture. The inter predictor, in operation, predictsa first set of samples for a first partition of a current picture withone or more motion vectors including a first motion vector and predictsa second set of samples for a first portion of the first partition withone or more motion vectors from a second partition different from thefirst partition. The samples of the first set of samples of the firstportion of the first partition and of the second set of samples of thefirst portion of the first partition are weighted. A motion vector forthe first portion of the first partition is stored which is based on oneor both of the first motion vector and the second motion vector. Thefirst partition is decoded using at least the weighted samples of thefirst portion of the first partition.

In one aspect, an decoding method comprises predicting a first set ofsamples for a first partition of a current picture with one or moremotion vectors including a first motion vector and predicting a secondset of samples for a first portion of the first partition with one ormore motion vectors from a second partition different from the firstpartition. The samples of the first set of samples of the first portionof the first partition and of the second set of samples of the firstportion of the first partition are weighted. A motion vector for thefirst portion of the first partition is stored which is based on one orboth of the first motion vector and the second motion vector. The firstpartition is decoded using at least the weighted samples of the firstportion of the first partition.

Some implementations of embodiments of the present disclosure mayimprove an encoding efficiency, may simply be an encoding/decodingprocess, may accelerate an encoding/decoding process speed, mayefficiently select appropriate components/operations used in encodingand decoding such as appropriate filter, block size, motion vector,reference picture, reference block, etc.

Additional benefits and advantages of the disclosed embodiments willbecome apparent from the specification and drawings. The benefits and/oradvantages may be individually obtained by the various embodiments andfeatures of the specification and drawings, not all of which need to beprovided in order to obtain one or more of such benefits and/oradvantages.

It should be noted that general or specific embodiments may beimplemented as a system, a method, an integrated circuit, a computerprogram, a storage medium, or any selective combination thereof.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a functional configuration of anencoder according to an embodiment.

FIG. 2 is a flow chart indicating one example of an overall encodingprocess performed by the encoder.

FIG. 3 is a conceptual diagram illustrating one example of blocksplitting.

FIG. 4A is a conceptual diagram illustrating one example of a sliceconfiguration.

FIG. 4B is a conceptual diagram illustrating one example of a tileconfiguration.

FIG. 5A is a chart indicating transform basis functions for varioustransform types.

FIG. 5B is a conceptual diagram illustrating example spatially varyingtransforms (SVT).

FIG. 6A is a conceptual diagram illustrating one example of a filtershape used in an adaptive loop filter (ALF).

FIG. 6B is a conceptual diagram illustrating another example of a filtershape used in an ALF.

FIG. 6C is a conceptual diagram illustrating another example of a filtershape used in an ALF.

FIG. 7 is a block diagram indicating one example of a specificconfiguration of a loop filter which functions as a deblocking filter(DBF).

FIG. 8 is a conceptual diagram indicating an example of a deblockingfilter having a symmetrical filtering characteristic with respect to ablock boundary.

FIG. 9 is a conceptual diagram for illustrating a block boundary onwhich a deblocking filter process is performed.

FIG. 10 is a conceptual diagram indicating examples of Bs values.

FIG. 11 is a flow chart illustrating one example of a process performedby a prediction processor of the encoder.

FIG. 12 is a flow chart illustrating another example of a processperformed by the prediction processor of the encoder.

FIG. 13 is a flow chart illustrating another example of a processperformed by the prediction processor of the encoder.

FIG. 14 is a conceptual diagram illustrating sixty-seven intraprediction modes used in intra prediction in an embodiment.

FIG. 15 is a flow chart illustrating an example basic processing flow ofinter prediction.

FIG. 16 is a flow chart illustrating one example of derivation of motionvectors.

FIG. 17 is a flow chart illustrating another example of derivation ofmotion vectors.

FIG. 18 is a flow chart illustrating another example of derivation ofmotion vectors.

FIG. 19 is a flow chart illustrating an example of inter prediction innormal inter mode.

FIG. 20 is a flow chart illustrating an example of inter prediction inmerge mode.

FIG. 21 is a conceptual diagram for illustrating one example of a motionvector derivation process in merge mode.

FIG. 22 is a flow chart illustrating one example of frame rate upconversion (FRUC) process.

FIG. 23 is a conceptual diagram for illustrating one example of patternmatching (bilateral matching) between two blocks along a motiontrajectory.

FIG. 24 is a conceptual diagram for illustrating one example of patternmatching (template matching) between a template in a current picture anda block in a reference picture.

FIG. 25A is a conceptual diagram for illustrating one example ofderiving a motion vector of each sub-block based on motion vectors of aplurality of neighboring blocks.

FIG. 25B is a conceptual diagram for illustrating one example ofderiving a motion vector of each sub-block in affine mode in which threecontrol points are used.

FIG. 26A is a conceptual diagram for illustrating an affine merge mode.

FIG. 26B is a conceptual diagram for illustrating an affine merge modein which two control points are used.

FIG. 26C is a conceptual diagram for illustrating an affine merge modein which three control points are used.

FIG. 27 is a flow chart illustrating one example of a process in affinemerge mode.

FIG. 28A is a conceptual diagram for illustrating an affine inter modein which two control points are used.

FIG. 28B is a conceptual diagram for illustrating an affine inter modein which three control points are used.

FIG. 29 is a flow chart illustrating one example of a process in affineinter mode.

FIG. 30A is a conceptual diagram for illustrating an affine inter modein which a current block has three control points and a neighboringblock has two control points.

FIG. 30B is a conceptual diagram for illustrating an affine inter modein which a current block has two control points and a neighboring blockhas three control points.

FIG. 31A is a flow chart illustrating a merge mode process includingdecoder motion vector refinement (DMVR).

FIG. 31B is a conceptual diagram for illustrating one example of a DMVRprocess.

FIG. 32 is a flow chart illustrating one example of generation of aprediction image.

FIG. 33 is a flow chart illustrating another example of generation of aprediction image.

FIG. 34 is a flow chart illustrating another example of generation of aprediction image.

FIG. 35 is a flow chart illustrating one example of a prediction imagecorrection process performed by an overlapped block motion compensation(OBMC) process.

FIG. 36 is a conceptual diagram for illustrating one example of aprediction image correction process performed by an OBMC process.

FIG. 37 is a conceptual diagram for illustrating generation of twotriangular prediction images.

FIG. 38 is conceptual diagram for illustrating a model assuming uniformlinear motion.

FIG. 39 is a conceptual diagram for illustrating one example of aprediction image generation method using a luminance correction processperformed by a local illumination compensation (LIC) process.

FIG. 40 is a block diagram illustrating a mounting example of theencoder.

FIG. 41 is a block diagram illustrating a functional configuration of adecoder according to an embodiment.

FIG. 42 is a flow chart illustrating one example of an overall decodingprocess performed by the decoder.

FIG. 43 is a flow chart illustrating one example of a process performedby a prediction processor of the decoder.

FIG. 44 is a flow chart illustrating another example of a processperformed by the prediction processor of the decoder.

FIG. 45 is a flow chart illustrating an example of inter prediction innormal inter mode in the decoder.

FIG. 46 is a block diagram illustrating a mounting example of thedecoder.

FIG. 47 is a flowchart illustrating an overall process flow of splittingan image block into a plurality of partitions including at least a firstpartition having a non-rectangular shape (e.g., a triangle) and a secondpartition and performing further processing according to one embodiment.

FIG. 48 illustrates two exemplary methods of splitting an image blockinto a first partition having a non-rectangular shape (e.g., a triangle)and a second partition (also having a non-rectangular shape in theillustrated examples).

FIG. 49 illustrates one example of a boundary smoothing processinvolving weighting first values of boundary pixels predicted based onthe first partition and second values of the boundary pixels predictedbased on the second partition.

FIG. 50 illustrates three further samples of a boundary smoothingprocess involving weighting first values of boundary pixels predictedbased on the first partition and second values of the boundary pixelspredicted based on the second partition.

FIG. 51 is a table of sample parameters (“first index values”) and setsof information respectively encoded by the parameters.

FIG. 52 is a table illustrating banalization of parameters (indexvalues).

FIG. 53 is a flowchart illustrating a process of splitting an imageblock into a plurality of partitions including a first partition havinga non-rectangular-shape and a second partition.

FIG. 54 illustrates examples of splitting an image block into aplurality of partitions including a first partition having anon-rectangular shape, which is a triangle in the illustrated examples,and a second partition.

FIG. 55 illustrates further examples of splitting an image block into aplurality of partitions including a first partition having anon-rectangular shape, which is a polygon with at least five sides andangles in the illustrated examples, and a second partition.

FIG. 56 is a flowchart illustrating a boundary smoothing processinvolving weighting first values of boundary pixels predicted based onthe first partition and second values of the boundary pixels predictedbased on the second partition.

FIG. 57A illustrates an example of a boundary smoothing process whereinboundary pixels for which first values to be weighted are predictedbased on the first partition and second values to be weighted arepredicted based on the second partition.

FIG. 57B illustrates an example of a boundary smoothing process whereinboundary pixels for which first values to be weighted are predictedbased on the first partition and second values to be weighted arepredicted based on the second partition.

FIG. 57C illustrates an example of a boundary smoothing process whereinboundary pixels for which first values to be weighted are predictedbased on the first partition and second values to be weighted arepredicted based on the second partition.

FIG. 57D illustrates an example of a boundary smoothing process whereinboundary pixels for which first values to be weighted are predictedbased on the first partition and second values to be weighted arepredicted based on the second partition.

FIG. 58 is a flowchart illustrating a method performed on the encoderside of splitting an image block into a plurality of partitionsincluding a first partition having a non-rectangular shape and a secondpartition, based on a partition parameter indicative of the splitting,and writing one or more parameters including the partition parameterinto a bitstream in entropy encoding.

FIG. 59 is a flowchart illustrating a method performed on the decoderside of parsing one or more parameters from a bitstream, which includesa partition parameter indicative of splitting of an image block into aplurality of partitions including a first partition having anon-rectangular shape and a second partition, and splitting the imageblock into the plurality of partitions based on the partition parameter,and decoding the first partition and the second partition.

FIG. 60 is a table of sample partition parameters (“first index values”)which respectively indicate splitting of an image block into a pluralityof partitions including a first partition having a non-rectangular shapeand a second partition, and sets of information that may be jointlyencoded by the partition parameters, respectively.

FIG. 61 is a table of sample combinations of a first parameter and asecond parameter, one of which being a partition parameter indicative ofsplitting of an image block into a plurality of partitions including afirst partition having a non-rectangular shape and a second partition.

FIG. 62 is a flow chart illustrating an example of a process flow ofpredicting a first set of samples for a first partition of a currentpicture with a first motion vector, predicting a second set of samplesfor a first portion included in the first partition with a second motionvector, weighting the first and second sets of samples, storing at leastone of the first and second motion vectors for the first partition, andencoding or decoding the first partition using the weighted samples, andperforming further processing according to one embodiment.

FIG. 63 is a conceptual diagram for illustrating exemplary methods ofsplitting an image block into a first partition and a second partition.

FIG. 64 is a conceptual diagram for illustrating adjacent andnon-adjacent spatially neighboring partitions of a first partition.

FIG. 65 is a conceptual diagram for illustrating uni-prediction andbi-prediction motion vector candidates for an image block.

FIG. 66 is a conceptual diagram for illustrating examples of a firstportion of a first partition and first and second sets of samples.

FIG. 67 is a conceptual diagram for illustrating a first portion of afirst partition, which is a portion of the first partition that overlapswith a portion of an adjacent partition.

FIG. 68 is a conceptual diagram for illustrating an example case where afirst motion vector and a second motion vector are uni-prediction motionvectors pointing to different pictures in different reference picturelists.

FIG. 69 is a conceptual diagram for illustrating an example case wherethe first motion vector and the second motion vector are uni-predictionmotion vectors pointing to pictures in a single reference picture list.

FIG. 70, FIG. 71 and FIG. 72 are conceptual diagrams for illustratingexample cases where the first motion vector and the second motion vectorare uni-prediction motion vectors pointing to the same reference picturein the same reference picture list.

FIG. 73 is a block diagram illustrating an overall configuration of acontent providing system for implementing a content distributionservice.

FIG. 74 is a conceptual diagram illustrating one example of an encodingstructure in scalable encoding.

FIG. 75 is a conceptual diagram illustrating one example of an encodingstructure in scalable encoding.

FIG. 76 is a conceptual diagram illustrating an example of a displayscreen of a web page.

FIG. 77 is a conceptual diagram illustrating an example of a displayscreen of a web page.

FIG. 78 is a block diagram illustrating one example of a smartphone.

FIG. 79 is a block diagram illustrating an example of a configuration ofa smartphone.

DETAILED DESCRIPTION

Hereinafter, embodiment(s) will be described with reference to thedrawings. Note that the embodiment(s) described below each show ageneral or specific example. The numerical values, shapes, materials,components, the arrangement and connection of the components, steps, therelation and order of the steps, etc., indicated in the followingembodiment(s) are mere examples, and are not intended to limit the scopeof the claims.

Embodiments of an encoder and a decoder will be described below. Theembodiments are examples of an encoder and a decoder to which theprocesses and/or configurations presented in the description of aspectsof the present disclosure are applicable. The processes and/orconfigurations can also be implemented in an encoder and a decoderdifferent from those according to the embodiments. For example,regarding the processes and/or configurations as applied to theembodiments, any of the following may be implemented:

(1) Any of the components of the encoder or the decoder according to theembodiments presented in the description of aspects of the presentdisclosure may be substituted or combined with another componentpresented anywhere in the description of aspects of the presentdisclosure.

(2) In the encoder or the decoder according to the embodiments,discretionary changes may be made to functions or processes performed byone or more components of the encoder or the decoder, such as addition,substitution, removal, etc., of the functions or processes. For example,any function or process may be substituted or combined with anotherfunction or process presented anywhere in the description of aspects ofthe present disclosure.

(3) In methods implemented by the encoder or the decoder according tothe embodiments, discretionary changes may be made such as addition,substitution, and removal of one or more of the processes included inthe method. For example, any process in the method may be substituted orcombined with another process presented anywhere in the description ofaspects of the present disclosure.

(4) One or more components included in the encoder or the decoderaccording to embodiments may be combined with a component presentedanywhere in the description of aspects of the present disclosure, may becombined with a component including one or more functions presentedanywhere in the description of aspects of the present disclosure, andmay be combined with a component that implements one or more processesimplemented by a component presented in the description of aspects ofthe present disclosure.

(5) A component including one or more functions of the encoder or thedecoder according to the embodiments, or a component that implements oneor more processes of the encoder or the decoder according to theembodiments, may be combined or substituted with a component presentedanywhere in the description of aspects of the present disclosure, with acomponent including one or more functions presented anywhere in thedescription of aspects of the present disclosure, or with a componentthat implements one or more processes presented anywhere in thedescription of aspects of the present disclosure.

(6) In methods implemented by the encoder or the decoder according tothe embodiments, any of the processes included in the method may besubstituted or combined with a process presented anywhere in thedescription of aspects of the present disclosure or with anycorresponding or equivalent process.

(7) One or more processes included in methods implemented by the encoderor the decoder according to the embodiments may be combined with aprocess presented anywhere in the description of aspects of the presentdisclosure.

(8) The implementation of the processes and/or configurations presentedin the description of aspects of the present disclosure is not limitedto the encoder or the decoder according to the embodiments. For example,the processes and/or configurations may be implemented in a device usedfor a purpose different from the moving picture encoder or the movingpicture decoder disclosed in the embodiments.

[Encoder]

First, an encoder according to an embodiment will be described. FIG. 1is a block diagram illustrating a functional configuration of encoder100 according to the embodiment. Encoder 100 is a video encoder whichencodes a video in units of a block.

As illustrated in FIG. 1, encoder 100 is an apparatus which encodes animage in units of a block, and includes splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, block memory 118, loop filter120, frame memory 122, intra predictor 124, inter predictor 126, andprediction controller 128.

Encoder 100 is implemented as, for example, a generic processor andmemory. In this case, when a software program stored in the memory isexecuted by the processor, the processor functions as splitter 102,subtractor 104, transformer 106, quantizer 108, entropy encoder 110,inverse quantizer 112, inverse transformer 114, adder 116, loop filter120, intra predictor 124, inter predictor 126, and prediction controller128. Alternatively, encoder 100 may be implemented as one or morededicated electronic circuits corresponding to splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, an overall flow of processes performed by encoder 100 isdescribed, and then each of constituent elements included in encoder 100will be described.

[Overall Flow of Encoding Process]

FIG. 2 is a flow chart indicating one example of an overall encodingprocess performed by encoder 100.

First, splitter 102 of encoder 100 splits each of pictures included inan input image which is a video into a plurality of blocks having afixed size (e.g., 128×128 pixels) (Step Sa_1). Splitter 102 then selectsa splitting pattern for the fixed-size block (also referred to as ablock shape) (Step Sa_2). In other words, splitter 102 further splitsthe fixed-size block into a plurality of blocks which form the selectedsplitting pattern. Encoder 100 performs, for each of the plurality ofblocks, Steps Sa_3 to Sa_9 for the block (that is a current block to beencoded).

In other words, a prediction processor which includes all or part ofintra predictor 124, inter predictor 126, and prediction controller 128generates a prediction signal (also referred to as a prediction block)of the current block to be encoded (also referred to as a current block)(Step Sa_3).

Next, subtractor 104 generates a difference between the current blockand a prediction block as a prediction residual (also referred to as adifference block) (Step Sa_4).

Next, transformer 106 transforms the difference block and quantizer 108quantizes the result, to generate a plurality of quantized coefficients(Step Sa_5). It is to be noted that the block having the plurality ofquantized coefficients is also referred to as a coefficient block.

Next, entropy encoder 110 encodes (specifically, entropy encodes) thecoefficient block and a prediction parameter related to generation of aprediction signal to generate an encoded signal (Step Sa_6). It is to benoted that the encoded signal is also referred to as an encodedbitstream, a compressed bitstream, or a stream.

Next, inverse quantizer 112 performs inverse quantization of thecoefficient block and inverse transformer 114 performs inverse transformof the result, to restore a plurality of prediction residuals (that is,a difference block) (Step Sa_7).

Next, adder 116 adds the prediction block to the restored differenceblock to reconstruct the current block as a reconstructed image (alsoreferred to as a reconstructed block or a decoded image block) (StepSa_8). In this way, the reconstructed image is generated.

When the reconstructed image is generated, loop filter 120 performsfiltering of the reconstructed image as necessary (Step Sa_9).

Encoder 100 then determines whether encoding of the entire picture hasbeen finished (Step Sa_10). When determining that the encoding has notyet been finished (No in Step Sa_10), processes from Step Sa_2 areexecuted repeatedly.

Although encoder 100 selects one splitting pattern for a fixed-sizeblock, and encodes each block according to the splitting pattern in theabove-described example, it is to be noted that each block may beencoded according to a corresponding one of a plurality of splittingpatterns. In this case, encoder 100 may evaluate a cost for each of theplurality of splitting patterns, and, for example, may select theencoded signal obtainable by encoding according to the splitting patternwhich yields the smallest cost as an encoded signal which is output.

As illustrated, the processes in Steps Sa_1 to Sa_10 are performedsequentially by encoder 100. Alternatively, two or more of the processesmay be performed in parallel, the processes may be reordered, etc.

[Splitter]

Splitter 102 splits each of pictures included in an input video into aplurality of blocks, and outputs each block to subtractor 104. Forexample, splitter 102 first splits a picture into blocks of a fixed size(for example, 128×128). Other fixed block sizes may be employed. Thefixed-size block is also referred to as a coding tree unit (CTU).Splitter 102 then splits each fixed-size block into blocks of variablesizes (for example, 64×64 or smaller), based on recursive quadtreeand/or binary tree block splitting. In other words, splitter 102 selectsa splitting pattern. The variable-size block is also referred to as acoding unit (CU), a prediction unit (PU), or a transform unit (TU). Itis to be noted that, in various kinds of processing examples, there isno need to differentiate between CU, PU, and TU; all or some of theblocks in a picture may be processed in units of a CU, a PU, or a TU.

FIG. 3 is a conceptual diagram illustrating one example of blocksplitting according to an embodiment. In FIG. 3, the solid linesrepresent block boundaries of blocks split by quadtree block splitting,and the dashed lines represent block boundaries of blocks split bybinary tree block splitting.

Here, block 10 is a square block having 128×128 pixels (128×128 block).This 128×128 block 10 is first split into four square 64×64 blocks(quadtree block splitting).

The upper-left 64×64 block is further vertically split into tworectangular 32×64 blocks, and the left 32×64 block is further verticallysplit into two rectangular 16×64 blocks (binary tree block splitting).As a result, the upper-left 64×64 block is split into two 16×64 blocks11 and 12 and one 32×64 block 13.

The upper-right 64×64 block is horizontally split into two rectangular64×32 blocks 14 and 15 (binary tree block splitting).

The lower-left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The upper-left block and the lower-rightblock among the four 32×32 blocks are further split. The upper-left32×32 block is vertically split into two rectangle 16×32 blocks, and theright 16×32 block is further horizontally split into two 16×16 blocks(binary tree block splitting). The lower-right 32×32 block ishorizontally split into two 32×16 blocks (binary tree block splitting).As a result, the lower-left 64×64 block is split into 16×32 block 16,two 16×16 blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16blocks 21 and 22.

The lower-right 64×64 block 23 is not split.

As described above, in FIG. 3, block 10 is split into thirteenvariable-size blocks 11 through 23 based on recursive quadtree andbinary tree block splitting. This type of splitting is also referred toas quadtree plus binary tree (QTBT) splitting.

It is to be noted that, in FIG. 3, one block is split into four or twoblocks (quadtree or binary tree block splitting), but splitting is notlimited to these examples. For example, one block may be split intothree blocks (ternary block splitting). Splitting including such ternaryblock splitting is also referred to as multi-type tree (MBT) splitting.

[Picture Structure: Slice/Tile]

A picture may be configured in units of one or more slices or tiles inorder to decode the picture in parallel. The picture configured in unitsof one or more slices or tiles may be configured by splitter 102.

Slices are basic encoding units included in a picture. A picture mayinclude, for example, one or more slices. In addition, a slice includesone or more successive coding tree units (CTU).

FIG. 4A is a conceptual diagram illustrating one example of a sliceconfiguration. For example, a picture includes 11×8 CTUs and is splitinto four slices (slices 1 to 4). Slice 1 includes sixteen CTUs, slice 2includes twenty-one CTUs, slice 3 includes twenty-nine CTUs, and slice 4includes twenty-two CTUs. Here, each CTU in the picture belongs to oneof the slices. The shape of each slice is a shape obtainable bysplitting the picture horizontally. A boundary of each slice does notneed to be coincide with an image end, and may be coincide with any ofthe boundaries between CTUs in the image. The processing order of theCTUs in a slice (an encoding order or a decoding order) is, for example,a raster-scan order. A slice includes header information and encodeddata. Features of the slice may be described in header information. Thefeatures include a CTU address of a top CTU in the slice, a slice type,etc.

A tile is a unit of a rectangular region included in a picture. Each oftiles may be assigned with a number referred to as TileId in raster-scanorder.

FIG. 4B is a conceptual diagram indicating an example of a tileconfiguration. For example, a picture includes 11×8 CTUs and is splitinto four tiles of rectangular regions (tiles 1 to 4). When tiles areused, the processing order of CTUs are changed from the processing orderin the case where no tile is used. When no tile is used, CTUs in apicture are processed in raster-scan order. When tiles are used, atleast one CTU in each of the tiles is processed in raster-scan order.For example, as illustrated in FIG. 4B, the processing order of the CTUsincluded in tile 1 is the order which starts from the left-end of thefirst row of tile 1 toward the right-end of the first row of tile 1 andthen starts from the left-end of the second row of tile 1 toward theright-end of the second row of tile 1.

It is to be noted that the one tile may include one or more slices, andone slice may include one or more tiles.

[Subtractor]

Subtractor 104 subtracts a prediction signal (prediction sample that isinput from prediction controller 128 indicated below) from an originalsignal (original sample) in units of a block input from splitter 102 andsplit by splitter 102. In other words, subtractor 104 calculatesprediction errors (also referred to as residuals) of a block to beencoded (hereinafter also referred to as a current block). Subtractor104 then outputs the calculated prediction errors (residuals) totransformer 106.

The original signal is a signal which has been input into encoder 100and represents an image of each picture included in a video (forexample, a luma signal and two chroma signals). Hereinafter, a signalrepresenting an image is also referred to as a sample.

[Transformer]

Transformer 106 transforms prediction errors in spatial domain intotransform coefficients in frequency domain, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a defined discrete cosine transform (DCT) ordiscrete sine transform (DST) to prediction errors in spatial domain.The defined DCT or DST may be predefined.

It is to be noted that transformer 106 may adaptively select a transformtype from among a plurality of transform types, and transform predictionerrors into transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 5A is a chart indicating transform basisfunctions for the example transform types. In FIG. 5A, N indicates thenumber of input pixels. For example, selection of a transform type fromamong the plurality of transform types may depend on a prediction type(one of intra prediction and inter prediction), and may depend on anintra prediction mode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an EMT flag or an AMT flag) and information indicating theselected transform type is normally signaled at the CU level. It is tobe noted that the signaling of such information does not necessarilyneed to be performed at the CU level, and may be performed at anotherlevel (for example, at the bit sequence level, picture level, slicelevel, tile level, or CTU level).

In addition, transformer 106 may re-transform the transform coefficients(transform result). Such re-transform is also referred to as adaptivesecondary transform (AST) or non-separable secondary transform (NSST).For example, transformer 106 performs re-transform in units of asub-block (for example, 4×4 sub-block) included in a transformcoefficient block corresponding to an intra prediction error.Information indicating whether to apply NSST and information related toa transform matrix for use in NSST are normally signaled at the CUlevel. It is to be noted that the signaling of such information does notnecessarily need to be performed at the CU level, and may be performedat another level (for example, at the sequence level, picture level,slice level, tile level, or CTU level).

Transformer 106 may employ a separable transform and a non-separabletransform. A separable transform is a method in which a transform isperformed a plurality of times by separately performing a transform foreach of a number of directions according to the number of dimensions ofinputs. A non-separable transform is a method of performing a collectivetransform in which two or more dimensions in multidimensional inputs arecollectively regarded as a single dimension.

In one example of a non-separable transform, when an input is a 4×4block, the 4×4 block is regarded as a single array including sixteenelements, and the transform applies a 16×16 transform matrix to thearray.

In another example of a non-separable transform, a 4×4 input block isregarded as a single array including sixteen elements, and then atransform (hypercube givens transform) in which givens revolution isperformed on the array a plurality of times may be performed.

In the transform in transformer 106, the types of bases to betransformed into the frequency domain according to regions in a CU canbe switched. Examples include spatially varying transforms (SVT). InSVT, as illustrated in FIG. 5B, CUs are split into two equal regionshorizontally or vertically, and only one of the regions is transformedinto the frequency domain. A transform basis type can be set for eachregion. For example, DST7 and DST8 are used. In this example, only oneof these two regions in the CU is transformed, and the other is nottransformed. However, both of these two regions may be transformed. Inaddition, the splitting method is not limited to the splitting into twoequal regions, and can be more flexible. For example, the CU may besplit into four equal regions, or information indicating splitting maybe encoded separately and be signaled in the same manner as the CUsplitting. It is to be noted that SVT is also referred to as sub-blocktransform (SBT).

[Quantizer]

Quantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in a determinedscanning order, the transform coefficients of the current block, andquantizes the scanned transform coefficients based on quantizationparameters (QP) corresponding to the transform coefficients. Quantizer108 then outputs the quantized transform coefficients (hereinafter alsoreferred to as quantized coefficients) of the current block to entropyencoder 110 and inverse quantizer 112. The determined scanning order maybe predetermined.

A determined scanning order is an order for quantizing/inversequantizing transform coefficients. For example, a determined scanningorder may be defined as ascending order of frequency (from low to highfrequency) or descending order of frequency (from high to lowfrequency).

A quantization parameter (QP) is a parameter defining a quantizationstep (quantization width). For example, when the value of thequantization parameter increases, the quantization step also increases.In other words, when the value of the quantization parameter increases,the quantization error increases.

In addition, a quantization matrix may be used for quantization. Forexample, several kinds of quantization matrices may be usedcorrespondingly to frequency transform sizes such as 4×4 and 8×8,prediction modes such as intra prediction and inter prediction, andpixel components such as luma and chroma pixel components. It is to benoted that quantization means digitalizing values sampled at determinedintervals correspondingly to determined levels. In this technical field,quantization may be referred to using other expressions, such asrounding and scaling, and may employ rounding and scaling. Thedetermined intervals and levels may be predetermined.

Methods using quantization matrices include a method using aquantization matrix which has been set directly at the encoder side anda method using a quantization matrix which has been set as a default(default matrix). At the encoder side, a quantization matrix suitablefor features of an image can be set by directly setting a quantizationmatrix. This case, however, has a disadvantage of increasing a codingamount for encoding the quantization matrix.

There is a method for quantizing a high-frequency coefficient and alow-frequency coefficient without using a quantization matrix. It is tobe noted that this method is equivalent to a method using a quantizationmatrix (flat matrix) whose coefficients have the same value.

The quantization matrix may be specified using, for example, a sequenceparameter set (SPS) or a picture parameter set (PPS). The SPS includes aparameter which is used for a sequence, and the PPS includes a parameterwhich is used for a picture. Each of the SPS and the PPS may be simplyreferred to as a parameter set.

[Entropy Encoder]

Entropy encoder 110 generates an encoded signal (encoded bitstream)based on quantized coefficients which have been input from quantizer108. More specifically, entropy encoder 110, for example, binarizesquantized coefficients, and arithmetically encodes the binary signal,and outputs a compressed bit stream or sequence.

[Inverse Quantizer]

Inverse quantizer 112 inverse quantizes quantized coefficients whichhave been input from quantizer 108. More specifically, inverse quantizer112 inverse quantizes, in a determined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114. The determined scanning order may bepredetermined.

[Inverse Transformer]

Inverse transformer 114 restores prediction errors (residuals) byinverse transforming transform coefficients which have been input frominverse quantizer 112. More specifically, inverse transformer 114restores the prediction errors of the current block by applying aninverse transform corresponding to the transform applied by transformer106 on the transform coefficients. Inverse transformer 114 then outputsthe restored prediction errors to adder 116.

It is to be noted that since information is lost in quantization, therestored prediction errors do not match the prediction errors calculatedby subtractor 104. In other words, the restored prediction errorsnormally include quantization errors.

[Adder]

Adder 116 reconstructs the current block by adding prediction errorswhich have been input from inverse transformer 114 and predictionsamples which have been input from prediction controller 128. Adder 116then outputs the reconstructed block to block memory 118 and loop filter120. A reconstructed block is also referred to as a local decoded block.

[Block Memory]

Block memory 118 is, for example, storage for storing blocks in apicture to be encoded (hereinafter referred to as a current picture)which is referred to in intra prediction. More specifically, blockmemory 118 stores reconstructed blocks output from adder 116.

[Frame Memory]

Frame memory 122 is, for example, storage for storing reference picturesfor use in inter prediction, and is also referred to as a frame buffer.More specifically, frame memory 122 stores reconstructed blocks filteredby loop filter 120.

[Loop Filter]

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF or DBF), a sampleadaptive offset (SAO), and an adaptive loop filter (ALF).

In an ALF, a least square error filter for removing compressionartifacts is applied. For example, one filter selected from among aplurality of filters based on the direction and activity of localgradients is applied for each of 2×2 sub-blocks in the current block.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, fifteen or twenty-five classes). The classification of thesub-block is based on gradient directionality and activity. For example,classification index C (for example, C=5D+A) is derived based ongradient directionality D (for example, 0 to 2 or 0 to 4) and gradientactivity A (for example, 0 to 4). Then, based on classification index C,each sub-block is categorized into one out of a plurality of classes.

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by adding gradients of a plurality ofdirections and quantizing the result of addition.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in an ALF is, for example, a circularsymmetric filter shape. FIG. 6A through FIG. 6C illustrate examples offilter shapes used in ALFs. FIG. 6A illustrates a 5×5 diamond shapefilter, FIG. 6B illustrates a 7×7 diamond shape filter, and FIG. 6Cillustrates a 9×9 diamond shape filter. Information indicating thefilter shape is normally signaled at the picture level. It is to benoted that the signaling of such information indicating the filter shapedoes not necessarily need to be performed at the picture level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, CTU level, or CU level).

The ON or OFF of the ALF is determined, for example, at the picturelevel or CU level. For example, the decision of whether to apply the ALFto luma may be made at the CU level, and the decision of whether toapply ALF to chroma may be made at the picture level. Informationindicating ON or OFF of the ALF is normally signaled at the picturelevel or CU level. It is to be noted that the signaling of informationindicating ON or OFF of the ALF does not necessarily need to beperformed at the picture level or CU level, and may be performed atanother level (for example, at the sequence level, slice level, tilelevel, or CTU level).

The coefficient set for the plurality of selectable filters (forexample, fifteen or up to twenty-five filters) is normally signaled atthe picture level. It is to be noted that the signaling of thecoefficient set does not necessarily need to be performed at the picturelevel, and may be performed at another level (for example, at thesequence level, slice level, tile level, CTU level, CU level, orsub-block level).

[Loop Filter>Deblocking Filter]

In a deblocking filter, loop filter 120 performs a filter process on ablock boundary in a reconstructed image so as to reduce distortion whichoccurs at the block boundary.

FIG. 7 is a block diagram illustrating one example of a specificconfiguration of loop filter 120 which functions as a deblocking filter.

Loop filter 120 includes: boundary determiner 1201; filter determiner1203; filtering executor 1205; process determiner 1208; filtercharacteristic determiner 1207; and switches 1202, 1204, and 1206.

Boundary determiner 1201 determines whether a pixel to bedeblock-filtered (that is, a current pixel) is present around a blockboundary. Boundary determiner 1201 then outputs the determination resultto switch 1202 and processing determiner 1208.

In the case where boundary determiner 1201 has determined that a currentpixel is present around a block boundary, switch 1202 outputs anunfiltered image to switch 1204. In the opposite case where boundarydeterminer 1201 has determined that no current pixel is present around ablock boundary, switch 1202 outputs an unfiltered image to switch 1206.

Filter determiner 1203 determines whether to perform deblockingfiltering of the current pixel, based on the pixel value of at least onesurrounding pixel located around the current pixel. Filter determiner1203 then outputs the determination result to switch 1204 and processingdeterminer 1208.

In the case where filter determiner 1203 has determined to performdeblocking filtering of the current pixel, switch 1204 outputs theunfiltered image obtained through switch 1202 to filtering executor1205. In the opposite case were filter determiner 1203 has determinednot to perform deblocking filtering of the current pixel, switch 1204outputs the unfiltered image obtained through switch 1202 to switch1206.

When obtaining the unfiltered image through switches 1202 and 1204,filtering executor 1205 executes, for the current pixel, deblockingfiltering with the filter characteristic determined by filtercharacteristic determiner 1207. Filtering executor 1205 then outputs thefiltered pixel to switch 1206.

Under control by processing determiner 1208, switch 1206 selectivelyoutputs a pixel which has not been deblock-filtered and a pixel whichhas been deblock-filtered by filtering executor 1205.

Processing determiner 1208 controls switch 1206 based on the results ofdeterminations made by boundary determiner 1201 and filter determiner1203. In other words, processing determiner 1208 causes switch 1206 tooutput the pixel which has been deblock-filtered when boundarydeterminer 1201 has determined that the current pixel is present aroundthe block boundary and filter determiner 1203 has determined to performdeblocking filtering of the current pixel. In addition, other than theabove case, processing determiner 1208 causes switch 1206 to output thepixel which has not been deblock-filtered. A filtered image is outputfrom switch 1206 by repeating output of a pixel in this way.

FIG. 8 is a conceptual diagram indicating an example of a deblockingfilter having a symmetrical filtering characteristic with respect to ablock boundary.

In a deblocking filter process, one of two deblocking filters havingdifferent characteristics, that is, a strong filter and a weak filter isselected using pixel values and quantization parameters. In the case ofthe strong filter, pixels p0 to p2 and pixels q0 to q2 are presentacross a block boundary as illustrated in FIG. 8, the pixel values ofthe respective pixel q0 to q2 are changed to pixel values q′0 to q′2 byperforming, for example, computations according to the expressionsbelow.q′0=(p1+2×p0+2×q0+2×q1+q2+4)/8q′1=(p0+q0+q1+q2+2)/4q′2=(p0+q0+q1+3×q2+2×q3+4)/8

It is to be noted that, in the above expressions, p0 to p2 and q0 to q2are the pixel values of respective pixels p0 to p2 and pixels q0 to q2.In addition, q3 is the pixel value of neighboring pixel q3 located atthe opposite side of pixel q2 with respect to the block boundary. Inaddition, in the right side of each of the expressions, coefficientswhich are multiplied with the respective pixel values of the pixels tobe used for deblocking filtering are filter coefficients.

Furthermore, in the deblocking filtering, clipping may be performed sothat the calculated pixel values are not set over a threshold value. Inthe clipping process, the pixel values calculated according to the aboveexpressions are clipped to a value obtained according to “a computationpixel value±2×a threshold value” using the threshold value determinedbased on a quantization parameter. In this way, it is possible toprevent excessive smoothing.

FIG. 9 is a conceptual diagram for illustrating a block boundary onwhich a deblocking filter process is performed. FIG. 10 is a conceptualdiagram indicating examples of Bs values.

The block boundary on which the deblocking filter process is performedis, for example, a boundary between prediction units (PU) having 8×8pixel blocks as illustrated in FIG. 9 or a boundary between transformunits (TU). The deblocking filter process may be performed in units offour rows or four columns. First, boundary strength (Bs) values aredetermined as indicated in FIG. 10 for block P and block Q illustratedin FIG. 9.

According to the Bs values in FIG. 10, whether to perform deblockingfilter processes of block boundaries belonging to the same image usingdifferent strengths is determined. The deblocking filter process for achroma signal is performed when a Bs value is 2. The deblocking filterprocess for a luma signal is performed when a Bs value is 1 or more anda determined condition is satisfied. The determined condition may bepredetermined. It is to be noted that conditions for determining Bsvalues are not limited to those indicated in FIG. 10, and a Bs value maybe determined based on another parameter.

[Prediction Processor (Intra Predictor, Inter Predictor, PredictionController)]

FIG. 11 is a flow chart illustrating one example of a process performedby the prediction processor of encoder 100. It is to be noted that theprediction processor includes all or part of the following constituentelements: intra predictor 124; inter predictor 126; and predictioncontroller 128.

The prediction processor generates a prediction image of a current block(Step Sb_1). This prediction image is also referred to as a predictionsignal or a prediction block. It is to be noted that the predictionsignal is, for example, an intra prediction signal or an interprediction signal. Specifically, the prediction processor generates theprediction image of the current block using a reconstructed image whichhas been already obtained through generation of a prediction block,generation of a difference block, generation of a coefficient block,restoring of a difference block, and generation of a decoded imageblock.

The reconstructed image may be, for example, an image in a referencepicture, or an image of an encoded block in a current picture which isthe picture including the current block. The encoded block in thecurrent picture is, for example, a neighboring block of the currentblock.

FIG. 12 is a flow chart illustrating another example of a processperformed by the prediction processor of encoder 100.

The prediction processor generates a prediction image using a firstmethod (Step Sc_1 a), generates a prediction image using a second method(Step Sc_1 b), and generates a prediction image using a third method(Step Sc_1 c). The first method, the second method, and the third methodmay be mutually different methods for generating a prediction image.Each of the first to third methods may be an inter prediction method, anintra prediction method, or another prediction method. Theabove-described reconstructed image may be used in these predictionmethods.

Next, the prediction processor selects any one of a plurality ofprediction methods generated in Steps Sc_1 a, Sc_1 b, and Sc_1 c (StepSc 2). The selection of the prediction image, that is selection of amethod or a mode for obtaining a final prediction image may be made bycalculating a cost for each of the generated prediction images and basedon the cost. Alternatively, the selection of the prediction image may bemade based on a parameter which is used in an encoding process. Encoder100 may transform information for identifying a selected predictionimage, a method, or a mode into an encoded signal (also referred to asan encoded bitstream). The information may be, for example, a flag orthe like. In this way, the decoder is capable of generating a predictionimage according to the method or the mode selected based on theinformation in encoder 100. It is to be noted that, in the exampleillustrated in FIG. 12, the prediction processor selects any of theprediction images after the prediction images are generated using therespective methods. However, the prediction processor may select amethod or a mode based on a parameter for use in the above-describedencoding process before generating prediction images, and may generate aprediction image according to the method or mode selected.

For example, the first method and the second method may be intraprediction and inter prediction, respectively, and the predictionprocessor may select a final prediction image for a current block fromprediction images generated according to the prediction methods.

FIG. 13 is a flow chart illustrating another example of a processperformed by the prediction processor of encoder 100.

First, the prediction processor generates a prediction image using intraprediction (Step Sd_1 a), and generates a prediction image using interprediction (Step Sd_1 b). It is to be noted that the prediction imagegenerated by intra prediction is also referred to as an intra predictionimage, and the prediction image generated by inter prediction is alsoreferred to as an inter prediction image.

Next, the prediction processor evaluates each of the intra predictionimage and the inter prediction image (Step Sd_2). A cost may be used inthe evaluation. In other words, the prediction processor calculates costC for each of the intra prediction image and the inter prediction image.Cost C may be calculated according to an expression of an R-Doptimization model, for example, C=D+λ×R. In this expression, Dindicates a coding distortion of a prediction image, and is representedas, for example, a sum of absolute differences between the pixel valueof a current block and the pixel value of a prediction image. Inaddition, R indicates a predicted coding amount of a prediction image,specifically, the coding amount required to encode motion informationfor generating a prediction image, etc. In addition, λ indicates, forexample, a multiplier according to the method of Lagrange multiplier.

The prediction processor then selects the prediction image for which thesmallest cost C has been calculated among the intra prediction image andthe inter prediction image, as the final prediction image for thecurrent block (Step Sd_3). In other words, the prediction method or themode for generating the prediction image for the current block isselected.

[Intra Predictor]

Intra predictor 124 generates a prediction signal (intra predictionsignal) by performing intra prediction (also referred to as intra frameprediction) of the current block by referring to a block or blocks inthe current picture and stored in block memory 118. More specifically,intra predictor 124 generates an intra prediction signal by performingintra prediction by referring to samples (for example, luma and/orchroma values) of a block or blocks neighboring the current block, andthen outputs the intra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of intra prediction modes which have beendefined. The intra prediction modes include one or more non-directionalprediction modes and a plurality of directional prediction modes. Thedefined modes may be predefined.

The one or more non-directional prediction modes include, for example,the planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard.

The plurality of directional prediction modes include, for example, thethirty-three directional prediction modes defined in the H.265/HEVCstandard. It is to be noted that the plurality of directional predictionmodes may further include thirty-two directional prediction modes inaddition to the thirty-three directional prediction modes (for a totalof sixty-five directional prediction modes). FIG. 14 is a conceptualdiagram illustrating sixty-seven intra prediction modes in total thatmay be used in intra prediction (two non-directional prediction modesand sixty-five directional prediction modes). The solid arrows representthe thirty-three directions defined in the H.265/HEVC standard, and thedashed arrows represent the additional thirty-two directions (the twonon-directional prediction modes are not illustrated in FIG. 14).

In various kinds of processing examples, a luma block may be referred toin intra prediction of a chroma block. In other words, a chromacomponent of the current block may be predicted based on a lumacomponent of the current block. Such intra prediction is also referredto as cross-component linear model (CCLM) prediction. The intraprediction mode for a chroma block in which such a luma block isreferred to (also referred to as, for example, a CCLM mode) may be addedas one of the intra prediction modes for chroma blocks.

Intra predictor 124 may correct intra-predicted pixel values based onhorizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC (referred to as, for example, a PDPC flag) isnormally signaled at the CU level. It is to be noted that the signalingof such information does not necessarily need to be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, or CTU level).

[Inter Predictor]

Inter predictor 126 generates a prediction signal (inter predictionsignal) by performing inter prediction (also referred to as inter frameprediction) of the current block by referring to a block or blocks in areference picture, which is different from the current picture and isstored in frame memory 122. Inter prediction is performed in units of acurrent block or a current sub-block (for example, a 4×4 block) in thecurrent block. For example, inter predictor 126 performs motionestimation in a reference picture for the current block or the currentsub-block, and finds out a reference block or a sub-block which bestmatches the current block or the current sub-block. Inter predictor 126then obtains motion information (for example, a motion vector) whichcompensates a motion or a change from the reference block or thesub-block to the current block or the sub-block. Inter predictor 126generates an inter prediction signal of the current block or thesub-block by performing motion compensation (or motion prediction) basedon the motion information. Inter predictor 126 outputs the generatedinter prediction signal to prediction controller 128.

The motion information used in motion compensation may be signaled asinter prediction signals in various forms. For example, a motion vectormay be signaled. As another example, the difference between a motionvector and a motion vector predictor may be signaled.

[Basic Flow of Inter Prediction]

FIG. 15 is a flow chart illustrating an example basic processing flow ofinter prediction.

First, inter predictor 126 generates a prediction signal (Steps Se_1 toSe_3). Next, subtractor 104 generates the difference between a currentblock and a prediction image as a prediction residual (Step Se_4).

Here, in the generation of the prediction image, inter predictor 126generates the prediction image through determination of a motion vector(MV) of the current block (Steps Se_1 and Se_2) and motion compensation(Step Se_3). Furthermore, in determination of an MV, inter predictor 126determines the MV through selection of a motion vector candidate (MVcandidate) (Step Se_1) and derivation of an MV (Step Se_2). Theselection of the MV candidate is made by, for example, selecting atleast one MV candidate from an MV candidate list. Alternatively, inderivation of an MV, inter predictor 126 may further select at least oneMV candidate from the at least one MV candidate, and determine theselected at least one MV candidate as the MV for the current block.Alternatively, inter predictor 126 may determine the MV for the currentblock by performing estimation in a reference picture region specifiedby each of the selected at least one MV candidate. It is to be notedthat the estimation in a reference picture region may be referred to asmotion estimation.

In addition, although Steps Se_1 to Se_3 are performed by interpredictor 126 in the above-described example, a process that is forexample Step Se_1, Step Se_2, or the like may be performed by anotherconstituent element included in encoder 100.

[Motion Vector Derivation Flow]

FIG. 16 is a flow chart illustrating one example of derivation of motionvectors.

Inter predictor 126 derives an MV of a current block in a mode forencoding motion information (for example, an MV). In this case, forexample, the motion information is encoded as a prediction parameter,and is signaled. In other words, the encoded motion information isincluded in an encoded signal (also referred to as an encodedbitstream).

Alternatively, inter predictor 126 derives an MV in a mode in whichmotion information is not encoded. In this case, no motion informationis included in an encoded signal.

Here, MV derivation modes may include a normal inter mode, a merge mode,a FRUC mode, an affine mode, etc. which are described later. Modes inwhich motion information is encoded among the modes include the normalinter mode, the merge mode, the affine mode (specifically, an affineinter mode and an affine merge mode), etc. It is to be noted that motioninformation may include not only an MV but also motion vector predictorselection information which is described later. Modes in which no motioninformation is encoded include the FRUC mode, etc. Inter predictor 126selects a mode for deriving an MV of the current block from the modes,and derives the MV of the current block using the selected mode.

FIG. 17 is a flow chart illustrating another example of derivation ofmotion vectors.

Inter predictor 126 derives an MV of a current block in a mode in whichan MV difference is encoded. In this case, for example, the MVdifference is encoded as a prediction parameter, and is signaled. Inother words, the encoded MV difference is included in an encoded signal.The MV difference is the difference between the MV of the current blockand the MV predictor.

Alternatively, inter predictor 126 derives an MV in a mode in which noMV difference is encoded. In this case, no encoded MV difference isincluded in an encoded signal.

Here, as described above, the MV derivation modes include the normalinter mode, the merge mode, the FRUC mode, the affine mode, etc. whichare described later. Modes in which an MV difference is encoded amongthe modes include the normal inter mode, the affine mode (specifically,the affine inter mode), etc. Modes in which no MV difference is encodedinclude the FRUC mode, the merge mode, the affine mode (specifically,the affine merge mode), etc. Inter predictor 126 selects a mode forderiving an MV of the current block from the plurality of modes, andderives the MV of the current block using the selected mode.

[Motion Vector Derivation Flow]

FIG. 18 is a flow chart illustrating another example of derivation ofmotion vectors. The MV derivation modes which are inter prediction modesinclude a plurality of modes and are roughly divided into modes in whichan MV difference is encoded and modes in which no motion vectordifference is encoded. The modes in which no MV difference is encodedinclude the merge mode, the FRUC mode, the affine mode (specifically,the affine merge mode), etc. These modes are described in detail later.Simply, the merge mode is a mode for deriving an MV of a current blockby selecting a motion vector from an encoded surrounding block, and theFRUC mode is a mode for deriving an MV of a current block by performingestimation between encoded regions. The affine mode is a mode forderiving, as an MV of a current block, a motion vector of each of aplurality of sub-blocks included in the current block, assuming affinetransform.

More specifically, as illustrated when the inter prediction modeinformation indicates 0 (0 in Sf_1), inter predictor 126 derives amotion vector using the merge mode (Sf_2). When the inter predictionmode information indicates 1 (1 in Sf_1), inter predictor 126 derives amotion vector using the FRUC mode (Sf_3). When the inter prediction modeinformation indicates 2 (2 in Sf_1), inter predictor 126 derives amotion vector using the affine mode (specifically, the affine mergemode) (Sf_4). When the inter prediction mode information indicates 3 (3in Sf_1), inter predictor 126 derives a motion vector using a mode inwhich an MV difference is encoded (for example, a normal inter mode(Sf_5).

[MV Derivation>Normal Inter Mode]

The normal inter mode is an inter prediction mode for deriving an MV ofa current block based on a block similar to the image of the currentblock from a reference picture region specified by an MV candidate. Inthis normal inter mode, an MV difference is encoded.

FIG. 19 is a flow chart illustrating an example of inter prediction innormal inter mode.

First, inter predictor 126 obtains a plurality of MV candidates for acurrent block based on information such as MVs of a plurality of encodedblocks temporally or spatially surrounding the current block (StepSg_1). In other words, inter predictor 126 generates an MV candidatelist.

Next, inter predictor 126 extracts N (an integer of 2 or larger) MVcandidates from the plurality of MV candidates obtained in Step Sg_1, asmotion vector predictor candidates (also referred to as MV predictorcandidates) according to a determined priority order (Step Sg_2). It isto be noted that the priority order may be determined in advance foreach of the N MV candidates.

Next, inter predictor 126 selects one motion vector predictor candidatefrom the N motion vector predictor candidates, as the motion vectorpredictor (also referred to as an MV predictor) of the current block(Step Sg_3). At this time, inter predictor 126 encodes, in a stream,motion vector predictor selection information for identifying theselected motion vector predictor. It is to be noted that the stream isan encoded signal or an encoded bitstream as described above.

Next, inter predictor 126 derives an MV of a current block by referringto an encoded reference picture (Step Sg_4). At this time, interpredictor 126 further encodes, in the stream, the difference valuebetween the derived MV and the motion vector predictor as an MVdifference. It is to be noted that the encoded reference picture is apicture including a plurality of blocks which have been reconstructedafter being encoded.

Lastly, inter predictor 126 generates a prediction image for the currentblock by performing motion compensation of the current block using thederived MV and the encoded reference picture (Step Sg_5). It is to benoted that the prediction image is an inter prediction signal asdescribed above.

In addition, information indicating the inter prediction mode (normalinter mode in the above example) used to generate the prediction imageis, for example, encoded as a prediction parameter.

It is to be noted that the MV candidate list may be also used as a listfor use in another mode. In addition, the processes related to the MVcandidate list may be applied to processes related to the list for usein another mode. The processes related to the MV candidate list include,for example, extraction or selection of an MV candidate from the MVcandidate list, reordering of MV candidates, or deletion of an MVcandidate.

[MV Derivation>Merge Mode]

The merge mode is an inter prediction mode for selecting an MV candidatefrom an MV candidate list as an MV of a current block, thereby derivingthe MV.

FIG. 20 is a flow chart illustrating an example of inter prediction inmerge mode.

First, inter predictor 126 obtains a plurality of MV candidates for acurrent block based on information such as MVs of a plurality of encodedblocks temporally or spatially surrounding the current block (StepSh_1). In other words, inter predictor 126 generates an MV candidatelist.

Next, inter predictor 126 selects one MV candidate from the plurality ofMV candidates obtained in Step Sh_1, thereby deriving an MV of thecurrent block (Step Sh_2). At this time, inter predictor 126 encodes, ina stream, MV selection information for identifying the selected MVcandidate.

Lastly, inter predictor 126 generates a prediction image for the currentblock by performing motion compensation of the current block using thederived MV and the encoded reference picture (Step Sh_3).

In addition, information indicating the inter prediction mode (mergemode in the above example) used to generate the prediction image andincluded in the encoded signal is, for example, encoded as a predictionparameter.

FIG. 21 is a conceptual diagram for illustrating one example of a motionvector derivation process of a current picture in merge mode.

First, an MV candidate list in which MV predictor candidates areregistered is generated. Examples of MV predictor candidates include:spatially neighboring MV predictors which are MVs of a plurality ofencoded blocks located spatially surrounding a current block; temporallyneighboring MV predictors which are MVs of surrounding blocks on whichthe position of a current block in an encoded reference picture isprojected; combined MV predictors which are MVs generated by combiningthe MV value of a spatially neighboring MV predictor and the MV of atemporally neighboring MV predictor; and a zero MV predictor which is anMV having a zero value.

Next, one MV predictor is selected from a plurality of MV predictorsregistered in an MV predictor list, and the selected MV predictor isdetermined as the MV of a current block.

Furthermore, the variable length encoder describes and encodes, in astream, merge_idx which is a signal indicating which MV predictor hasbeen selected.

It is to be noted that the MV predictors registered in the MV predictorlist described in FIG. 21 are examples. The number of MV predictors maybe different from the number of MV predictors in the diagram, the MVpredictor list may be configured in such a manner that some of the kindsof the MV predictors in the diagram may not be included, or that one ormore MV predictors other than the kinds of MV predictors in the diagramare included.

A final MV may be determined by performing a decoder motion vectorrefinement process (DMVR) to be described later using the MV of thecurrent block derived in merge mode.

It is to be noted that the MV predictor candidates are MV candidatesdescribed above, and the MV predictor list is the MV candidate listdescribed above. It is to be noted that the MV candidate list may bereferred to as a candidate list. In addition, merge_idx is MV selectioninformation.

[MV Derivation>FRUC Mode]

Motion information may be derived at the decoder side without beingsignaled from the encoder side. It is to be noted that, as describedabove, the merge mode defined in the H.265/HEVC standard may be used. Inaddition, for example, motion information may be derived by performingmotion estimation at the decoder side. In an embodiment, at the decoderside, motion estimation is performed without using any pixel value in acurrent block.

Here, a mode for performing motion estimation at the decoder side isdescribed. The mode for performing motion estimation at the decoder sidemay be referred to as a pattern matched motion vector derivation (PMMVD)mode, or a frame rate up-conversion (FRUC) mode.

One example of a FRUC process in the form of a flow chart is illustratedin FIG. 22. First, a list of a plurality of candidates each having amotion vector (MV) predictor (that is, an MV candidate list that may bealso used as a merge list) is generated by referring to a motion vectorin an encoded block which spatially or temporally neighbors a currentblock (Step Si_1). Next, a best MV candidate is selected from theplurality of MV candidates registered in the MV candidate list (StepSi_2). For example, the evaluation values of the respective MVcandidates included in the MV candidate list are calculated, and one MVcandidate is selected based on the evaluation values. Based on theselected motion vector candidates, a motion vector for the current blockis then derived (Step Si_4). More specifically, for example, theselected motion vector candidate (best MV candidate) is derived directlyas the motion vector for the current block. In addition, for example,the motion vector for the current block may be derived using patternmatching in a surrounding region of a position in a reference picturewhere the position in the reference picture corresponds to the selectedmotion vector candidate. In other words, estimation using the patternmatching and the evaluation values may be performed in the surroundingregion of the best MV candidate, and when there is an MV that yields abetter evaluation value, the best MV candidate may be updated to the MVthat yields the better evaluation value, and the updated MV may bedetermined as the final MV for the current block. A configuration inwhich no such a process for updating the best MV candidate to the MVhaving a better evaluation value is performed is also possible.

Lastly, inter predictor 126 generates a prediction image for the currentblock by performing motion compensation of the current block using thederived MV and the encoded reference picture (Step Si_5).

A similar process may be performed in units of a sub-block.

Evaluation values may be calculated according to various kinds ofmethods. For example, a comparison is made between a reconstructed imagein a region in a reference picture corresponding to a motion vector anda reconstructed image in a determined region (the region may be, forexample, a region in another reference picture or a region in aneighboring block of a current picture, as indicated below). Thedetermined region may be predetermined.

The difference between the pixel values of the two reconstructed imagesmay be used for an evaluation value of the motion vectors. It is to benoted that an evaluation value may be calculated using information otherthan the value of the difference.

Next, an example of pattern matching is described in detail. First, oneMV candidate included in an MV candidate list (for example, a mergelist) is selected as a start point of estimation by the patternmatching. For example, as the pattern matching, either a first patternmatching or a second pattern matching may be used. The first patternmatching and the second pattern matching are also referred to asbilateral matching and template matching, respectively.

[MV Derivation>FRUC>Bilateral Matching]

In the first pattern matching, pattern matching is performed between twoblocks along a motion trajectory of a current block which are two blocksin different two reference pictures. Accordingly, in the first patternmatching, a region in another reference picture along the motiontrajectory of the current block is used as a determined region forcalculating the evaluation value of the above-described candidate. Thedetermined region may be predetermined.

FIG. 23 is a conceptual diagram for illustrating one example of thefirst pattern matching (bilateral matching) between the two blocks inthe two reference pictures along the motion trajectory. As illustratedin FIG. 23, in the first pattern matching, two motion vectors (MV0, MV1)are derived by estimating a pair which best matches among pairs in thetwo blocks in the two different reference pictures (Ref0, Ref1) whichare the two blocks along the motion trajectory of the current block (Curblock). More specifically, a difference between the reconstructed imageat a specified location in the first encoded reference picture (Ref0)specified by an MV candidate and the reconstructed image at a specifiedlocation in the second encoded reference picture (Ref1) specified by asymmetrical MV obtained by scaling the MV candidate at a display timeinterval is derived for the current block, and an evaluation value iscalculated using the value of the obtained difference. It is possible toselect, as the final MV, the MV candidate which yields the bestevaluation value among the plurality of MV candidates, and which islikely to produce good results.

In the assumption of a continuous motion trajectory, the motion vectors(MV0, MV1) specifying the two reference blocks are proportional totemporal distances (TD0, TD1) between the current picture (Cur Pic) andthe two reference pictures (Ref0, Ref1). For example, when the currentpicture is temporally located between the two reference pictures and thetemporal distances from the current picture to the respective tworeference pictures are equal to each other, mirror-symmetricalbi-directional motion vectors are derived in the first pattern matching.

[MV Derivation>FRUC>Template Matching]

In the second pattern matching (template matching), pattern matching isperformed between a block in a reference picture and a template in thecurrent picture (the template is a block neighboring the current blockin the current picture (the neighboring block is, for example, an upperand/or left neighboring block(s))). Accordingly, in the second patternmatching, the block neighboring the current block in the current pictureis used as the determined region for calculating the evaluation value ofthe above-described candidate.

FIG. 24 is a conceptual diagram for illustrating one example of patternmatching (template matching) between a template in a current picture anda block in a reference picture. As illustrated in FIG. 24, in the secondpattern matching, the motion vector of the current block (Cur block) isderived by estimating, in the reference picture (Ref0), the block whichbest matches the block neighboring the current block in the currentpicture (Cur Pic). More specifically, it is possible that the differencebetween a reconstructed image in an encoded region which neighbors bothleft and above or either left or above and a reconstructed image whichis in a corresponding region in the encoded reference picture (Ref0) andis specified by an MV candidate is derived, an evaluation value iscalculated using the value of the obtained difference, and the MVcandidate which yields the best evaluation value among a plurality of MVcandidates is selected as the best MV candidate.

Such information indicating whether to apply the FRUC mode (referred toas, for example, a FRUC flag) may be signaled at the CU level. Inaddition, when the FRUC mode is applied (for example, when a FRUC flagis true), information indicating an applicable pattern matching method(either the first pattern matching or the second pattern matching) maybe signaled at the CU level. It is to be noted that the signaling ofsuch information does not necessarily need to be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

[MV Derivation>Affine Mode]

Next, the affine mode for deriving a motion vector in units of asub-block based on motion vectors of a plurality of neighboring blocksis described. This mode is also referred to as an affine motioncompensation prediction mode.

FIG. 25A is a conceptual diagram for illustrating one example ofderiving a motion vector of each sub-block based on motion vectors of aplurality of neighboring blocks. In FIG. 25A, the current block includessixteen 4×4 sub-blocks. Here, motion vector V0 at an upper-left cornercontrol point in the current block is derived based on a motion vectorof a neighboring block, and likewise, motion vector V1 at an upper-rightcorner control point in the current block is derived based on a motionvector of a neighboring sub-block. Two motion vectors v0 and v1 may beprojected according to an expression (1A) indicated below, and motionvectors (vx, vy) for the respective sub-blocks in the current block maybe derived.

$\begin{matrix}\left\lbrack {{Math}.\mspace{14mu} 1} \right\rbrack & \; \\\left\{ \begin{matrix}{v_{x} = {{\frac{\left( {v_{1x} - v_{0x}} \right)}{w}x} - {\frac{\left( {v_{1y} - v_{0y}} \right)}{w}y} + v_{0x}}} \\{v_{y} = {{\frac{\left( {v_{1y} - v_{0y}} \right)}{w}x} - {\frac{\left( {v_{1x} - v_{0x}} \right)}{w}y} + v_{0y}}}\end{matrix} \right. & \left( {1A} \right)\end{matrix}$

Here, x and y indicate the horizontal position and the vertical positionof the sub-block, respectively, and w indicates a determined weightingcoefficient. The determined weighting coefficient may be predetermined.

Such information indicating the affine mode (for example, referred to asan affine flag) may be signaled at the CU level. It is to be noted thatthe signaling of the information indicating the affine mode does notnecessarily need to be performed at the CU level, and may be performedat another level (for example, at the sequence level, picture level,slice level, tile level, CTU level, or sub-block level).

In addition, the affine mode may include several modes for differentmethods for deriving motion vectors at the upper-left and upper-rightcorner control points. For example, the affine mode include two modeswhich are the affine inter mode (also referred to as an affine normalinter mode) and the affine merge mode.

[MV Derivation>Affine Mode]

FIG. 25B is a conceptual diagram for illustrating one example ofderiving a motion vector of each sub-block in affine mode in which threecontrol points are used. In FIG. 25B, the current block includes sixteen4×4 blocks. Here, motion vector V0 at the upper-left corner controlpoint for the current block is derived based on a motion vector of aneighboring block, and likewise, motion vector V1 at the upper-rightcorner control point for the current block is derived based on a motionvector of a neighboring block, and motion vector V2 at the lower-leftcorner control point for the current block is derived based on a motionvector of a neighboring block. Three motion vectors v0, v1, and v2 maybe projected according to an expression (1B) indicated below, and motionvectors (vx, vy) for the respective sub-blocks in the current block maybe derived.

$\begin{matrix}\left\lbrack {{Math}.\mspace{14mu} 2} \right\rbrack & \; \\\left\{ \begin{matrix}{v_{x} = {{\frac{\left( {v_{1x} - v_{0x}} \right)}{w}x} - {\frac{\left( {v_{2x} - v_{0x}} \right)}{h}y} + v_{0x}}} \\{v_{y} = {{\frac{\left( {v_{1y} - v_{0y}} \right)}{w}x} - {\frac{\left( {v_{2y} - v_{0y}} \right)}{h}y} + v_{0y}}}\end{matrix} \right. & \left( {1B} \right)\end{matrix}$

Here, x and y indicate the horizontal position and the vertical positionof the center of the sub-block, respectively, w indicates the width ofthe current block, and h indicates the height of the current block.

Affine modes in which different numbers of control points (for example,two and three control points) are used may be switched and signaled atthe CU level. It is to be noted that information indicating the numberof control points in affine mode used at the CU level may be signaled atanother level (for example, the sequence level, picture level, slicelevel, tile level, CTU level, or sub-block level).

In addition, such an affine mode in which three control points are usedmay include different methods for deriving motion vectors at theupper-left, upper-right, and lower-left corner control points. Forexample, the affine modes include two modes which are the affine intermode (also referred to as the affine normal inter mode) and the affinemerge mode.

[MV Derivation>Affine Merge Mode]

FIG. 26A, FIG. 26B, and FIG. 26C are conceptual diagrams forillustrating the affine merge mode.

As illustrated in FIG. 26A, in the affine merge mode, for example,motion vector predictors at respective control points of a current blockare calculated based on a plurality of motion vectors corresponding toblocks encoded according to the affine mode among encoded block A(left), block B (upper), block C (upper-right), block D (lower-left),and block E (upper-left) which neighbor the current block. Morespecifically, encoded block A (left), block B (upper), block C(upper-right), block D (lower-left), and block E (upper-left) arechecked in the listed order, and the first effective block encodedaccording to the affine mode is identified. Motion vector predictors atthe control points of the current block are calculated based on aplurality of motion vectors corresponding to the identified block.

For example, as illustrated in FIG. 26B, when block A which neighbors tothe left of the current block has been encoded according to an affinemode in which two control points are used, motion vectors v3 and v4projected at the upper-left corner position and the upper-right cornerposition of the encoded block including block A are derived. Motionvector predictor v0 at the upper-left corner control point of thecurrent block and motion vector predictor v1 at the upper-right cornercontrol point of the current block are then calculated from derivedmotion vectors v3 and v4.

For example, as illustrated in FIG. 26C, when block A which neighbors tothe left of the current block has been encoded according to an affinemode in which three control points are used, motion vectors v3, v4, andv5 projected at the upper-left corner position, the upper-right cornerposition, and the lower-left corner position of the encoded blockincluding block A are derived. Motion vector predictor v0 at theupper-left corner control point of the current block, motion vectorpredictor v1 at the upper-right corner control point of the currentblock, and motion vector predictor v2 at the lower-left corner controlpoint of the current block are then calculated from derived motionvectors v3, v4, and v5.

It is to be noted that this method for deriving motion vector predictorsmay be used to derive motion vector predictors of the respective controlpoints of the current block in Step Sj_1 in FIG. 29 described later.

FIG. 27 is a flow chart illustrating one example of the affine mergemode.

In affine merge mode as illustrated, first, inter predictor 126 derivesMV predictors of respective control points of a current block (StepSk_1). The control points are an upper-left corner point of the currentblock and an upper-right corner point of the current block asillustrated in FIG. 25A, or an upper-left corner point of the currentblock, an upper-right corner point of the current block, and alower-left corner point of the current block as illustrated in FIG. 25B.

In other words, as illustrated in FIG. 26A, inter predictor 126 checksencoded block A (left), block B (upper), block C (upper-right), block D(lower-left), and block E (upper-left) in the listed order, andidentifies the first effective block encoded according to the affinemode.

When block A is identified and block A has two control points, asillustrated in FIG. 26B, inter predictor 126 calculates motion vector v0at the upper-left corner control point of the current block and motionvector v1 at the upper-right corner control point of the current blockfrom motion vectors v3 and v4 at the upper-left corner and theupper-right corner of the encoded block including block A. For example,inter predictor 126 calculates motion vector v0 at the upper-left cornercontrol point of the current block and motion vector v1 at theupper-right corner control point of the current block by projectingmotion vectors v3 and v4 at the upper-left corner and the upper-rightcorner of the encoded block onto the current block.

Alternatively, when block A is identified and block A has three controlpoints, as illustrated in FIG. 26C, inter predictor 126 calculatesmotion vector v0 at the upper-left corner control point of the currentblock, motion vector v1 at the upper-right corner control point of thecurrent block, and motion vector v2 at the lower-left corner controlpoint of the current block from motion vectors v3, v4, and v5 at theupper-left corner, the upper-right corner, and the lower-left corner ofthe encoded block including block A. For example, inter predictor 126calculates motion vector v0 at the upper-left corner control point ofthe current block, motion vector v1 at the upper-right corner controlpoint of the current block, and motion vector v2 at the lower-leftcorner control point of the current block by projecting motion vectorsv3, v4, and v5 at the upper-left corner, the upper-right corner, and thelower-left corner of the encoded block onto the current block.

Next, inter predictor 126 performs motion compensation of each of aplurality of sub-blocks included in the current block. In other words,inter predictor 126 calculates, for each of the plurality of sub-blocks,a motion vector of the sub-block as an affine MV, by using either (i)two motion vector predictors v0 and v1 and the expression (1A) describedabove or (ii) three motion vector predictors v0, v1, and v2 and theexpression (1B) described above (Step Sk_2). Inter predictor 126 thenperforms motion compensation of the sub-blocks using these affine MVsand encoded reference pictures (Step Sk_3). As a result, motioncompensation of the current block is performed to generate a predictionimage of the current block.

[MV Derivation>Affine Inter Mode]

FIG. 28A is a conceptual diagram for illustrating an affine inter modein which two control points are used.

In the affine inter mode, as illustrated in FIG. 28A, a motion vectorselected from motion vectors of encoded block A, block B, and block Cwhich neighbor the current block is used as motion vector predictor v0at the upper-left corner control point of the current block. Likewise, amotion vector selected from motion vectors of encoded block D and blockE which neighbor the current block is used as motion vector predictor v1at the upper-right corner control point of the current block.

FIG. 28B is a conceptual diagram for illustrating an affine inter modein which three control points are used.

In the affine inter mode, as illustrated in FIG. 28B, a motion vectorselected from motion vectors of encoded block A, block B, and block Cwhich neighbor the current block is used as motion vector predictor v0at the upper-left corner control point of the current block. Likewise, amotion vector selected from motion vectors of encoded block D and blockE which neighbor the current block is used as motion vector predictor v1at the upper-right corner control point of the current block.Furthermore, a motion vector selected from motion vectors of encodedblock F and block G which neighbor the current block is used as motionvector predictor v2 at the lower-left corner control point of thecurrent block.

FIG. 29 is a flow chart illustrating one example of an affine intermode.

In the affine inter mode as illustrated, first, inter predictor 126derives MV predictors (v0, v1) or (v0, v1, v2) of respective two orthree control points of a current block (Step Sj_1). The control pointsare an upper-left corner point of the current block and an upper-rightcorner point of the current block as illustrated in FIG. 25A, or anupper-left corner point of the current block, an upper-right cornerpoint of the current block, and a lower-left corner point of the currentblock as illustrated in FIG. 25B.

In other words, inter predictor 126 derives the motion vector predictors(v0, v1) or (v0, v1, v2) of respective two or three control points ofthe current block by selecting motion vectors of any of the blocks amongencoded blocks in the vicinity of the respective control points of thecurrent block illustrated in either FIG. 28A or FIG. 28B. At this time,inter predictor 126 encodes, in a stream, motion vector predictorselection information for identifying the selected two motion vectors.

For example, inter predictor 126 may determine, using a cost evaluationor the like, the block from which a motion vector as a motion vectorpredictor at a control point is selected from among encoded blocksneighboring the current block, and may describe, in a bitstream, a flagindicating which motion vector predictor has been selected.

Next, inter predictor 126 performs motion estimation (Step Sj_3 andSj_4) while updating a motion vector predictor selected or derived inStep Sj_1 (Step Sj_2). In other words, inter predictor 126 calculates,as an affine MV, a motion vector of each of sub-blocks which correspondsto an updated motion vector predictor, using either the expression (1A)or expression (1B) described above (Step Sj_3). Inter predictor 126 thenperforms motion compensation of the sub-blocks using these affine MVsand encoded reference pictures (Step Sj_4). As a result, for example,inter predictor 126 determines the motion vector predictor which yieldsthe smallest cost as the motion vector at a control point in a motionestimation loop (Step Sj_5). At this time, inter predictor 126 furtherencodes, in the stream, the difference value between the determined MVand the motion vector predictor as an MV difference.

Lastly, inter predictor 126 generates a prediction image for the currentblock by performing motion compensation of the current block using thedetermined MV and the encoded reference picture (Step Sj_6).

[MV Derivation>Affine Inter Mode]

When affine modes in which different numbers of control points (forexample, two and three control points) are used may be switched andsignaled at the CU level, the number of control points in an encodedblock and the number of control points in a current block may bedifferent from each other. FIG. 30A and FIG. 30B are conceptual diagramsfor illustrating methods for deriving motion vector predictors atcontrol points when the number of control points in an encoded block andthe number of control points in a current block are different from eachother.

For example, as illustrated in FIG. 30A, when a current block has threecontrol points at the upper-left corner, the upper-right corner, and thelower-left corner, and block A which neighbors to the left of thecurrent block has been encoded according to an affine mode in which twocontrol points are used, motion vectors v3 and v4 projected at theupper-left corner position and the upper-right corner position in theencoded block including block A are derived. Motion vector predictor v0at the upper-left corner control point of the current block and motionvector predictor v1 at the upper-right corner control point of thecurrent block are then calculated from derived motion vectors v3 and v4.Furthermore, motion vector predictor v2 at the lower-left corner controlpoint is calculated from derived motion vectors v0 and v1.

For example, as illustrated in FIG. 30B, when a current block has twocontrol points at the upper-left corner and the upper-right corner, andblock A which neighbors to the left of the current block has beenencoded according to the affine mode in which three control points areused, motion vectors v3, v4, and v5 projected at the upper-left cornerposition, the upper-right corner position, and the lower-left cornerposition in the encoded block including block A are derived. Motionvector predictor v0 at the upper-left corner control point of thecurrent block and motion vector predictor v1 at the upper-right cornercontrol point of the current block are then calculated from derivedmotion vectors v3, v4, and v5.

It is to be noted that this method for deriving motion vector predictorsmay be used to derive motion vector predictors of the respective controlpoints of the current block in Step Sj_1 in FIG. 29.

[MV Derivation>DMVR]

FIG. 31A is a flow chart illustrating a relationship between the mergemode and DMVR.

Inter predictor 126 derives a motion vector of a current block accordingto the merge mode (Step Sl_1). Next, inter predictor 126 determineswhether to perform estimation of a motion vector, that is, motionestimation (Step Sl_2). Here, when determining not to perform motionestimation (No in Step Sl_2), inter predictor 126 determines the motionvector derived in Step Sl_1 as the final motion vector for the currentblock (Step Sl_4). In other words, in this case, the motion vector ofthe current block is determined according to the merge mode.

When determining to perform motion estimation in Step Sl_1 (Yes in StepSl_2), inter predictor 126 derives the final motion vector for thecurrent block by estimating a surrounding region of the referencepicture specified by the motion vector derived in Step Sl_1 (Step Sl_3).In other words, in this case, the motion vector of the current block isdetermined according to the DMVR.

FIG. 31B is a conceptual diagram for illustrating one example of a DMVRprocess for determining an MV.

First, (for example, in merge mode) the best MVP which has been set tothe current block is determined to be an MV candidate. A reference pixelis identified from a first reference picture (L0) which is an encodedpicture in the L0 direction according to an MV candidate (L0). Likewise,a reference pixel is identified from a second reference picture (L1)which is an encoded picture in the L1 direction according to an MVcandidate (L1). A template is generated by calculating an average ofthese reference pixels.

Next, each of the surrounding regions of MV candidates of the firstreference picture (L0) and the second reference picture (L1) areestimated, and the MV which yields the smallest cost is determined to bethe final MV. It is to be noted that the cost value may be calculated,for example, using a difference value between each of the pixel valuesin the template and a corresponding one of the pixel values in theestimation region, the values of MV candidates, etc.

It is to be noted that the processes, configurations, and operationsdescribed here typically are basically common between the encoder and adecoder to be described later.

Exactly the same example processes described here do not always need tobe performed. Any process for enabling derivation of the final MV byestimation in surrounding regions of MV candidates may be used.

[Motion Compensation>BIO/OBMC]

Motion compensation involves a mode for generating a prediction image,and correcting the prediction image. The mode is, for example, BIO andOBMC to be described later.

FIG. 32 is a flow chart illustrating one example of generation of aprediction image.

Inter predictor 126 generates a prediction image (Step Sm_1), andcorrects the prediction image, for example, according to any of themodes described above (Step Sm_2).

FIG. 33 is a flow chart illustrating another example of generation of aprediction image.

Inter predictor 126 determines a motion vector of a current block (StepSn_1). Next, inter predictor 126 generates a prediction image (StepSn_2), and determines whether to perform a correction process (StepSn_3). Here, when determining to perform a correction process (Yes inStep Sn_3), inter predictor 126 generates the final prediction image bycorrecting the prediction image (Step Sn_4). When determining not toperform a correction process (No in Step Sn_3), inter predictor 126outputs the prediction image as the final prediction image withoutcorrecting the prediction image (Step Sn_5).

In addition, motion compensation involves a mode for correcting aluminance of a prediction image when generating the prediction image.The mode is, for example, LIC to be described later.

FIG. 34 is a flow chart illustrating another example of generation of aprediction image.

Inter predictor 126 derives a motion vector of a current block (StepSo_1). Next, inter predictor 126 determines whether to perform aluminance correction process (Step So_2). Here, when determining toperform a luminance correction process (Yes in Step So_2), interpredictor 126 generates the prediction image while performing aluminance correction process (Step So_3). In other words, the predictionimage is generated using LIC. When determining not to perform aluminance correction process (No in Step So_2), inter predictor 126generates a prediction image by performing normal motion compensationwithout performing a luminance correction process (Step So_4).

[Motion Compensation>OBMC]

It is to be noted that an inter prediction signal may be generated usingmotion information for a neighboring block in addition to motioninformation for the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated in units of asub-block in the current block by performing a weighted addition of aprediction signal based on motion information obtained from motionestimation (in the reference picture) and a prediction signal based onmotion information for a neighboring block (in the current picture).Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In OBMC mode, information indicating a sub-block size for OBMC (referredto as, for example, an OBMC block size) may be signaled at the sequencelevel. Moreover, information indicating whether to apply the OBMC mode(referred to as, for example, an OBMC flag) may be signaled at the CUlevel. It is to be noted that the signaling of such information does notnecessarily need to be performed at the sequence level and CU level, andmay be performed at another level (for example, at the picture level,slice level, tile level, CTU level, or sub-block level).

Examples of the OBMC mode will be described in further detail. FIGS. 35and 36 are a flow chart and a conceptual diagram for illustrating anoutline of a prediction image correction process performed by an OBMCprocess.

First, as illustrated in FIG. 36, a prediction image (Pred) is obtainedthrough normal motion compensation using a motion vector (MV) assignedto the processing target (current) block. In FIG. 36, the arrow “MV”points a reference picture, and indicates what the current block of thecurrent picture refers to in order to obtain a prediction image.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV_L) which has been already derived for the encoded blockneighboring to the left of the current block to the current block(re-using the motion vector for the current block). The motion vector(MV_L) is indicated by an arrow “MV_L” indicating a reference picturefrom a current block. A first correction of a prediction image isperformed by overlapping two prediction images Pred and Pred_L. Thisprovides an effect of blending the boundary between neighboring blocks.

Likewise, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) which has been already derived for the encoded blockneighboring above the current block to the current block (re-using themotion vector for the current block). The motion vector (MV_U) isindicated by an arrow “MV_U” indicating a reference picture from acurrent block. A second correction of a prediction image is performed byoverlapping the prediction image Pred_U to the prediction images (forexample, Pred and Pred_L) on which the first correction has beenperformed. This provides an effect of blending the boundary betweenneighboring blocks. The prediction image obtained by the secondcorrection is the one in which the boundary between the neighboringblocks has been blended (smoothed), and thus is the final predictionimage of the current block.

Although the above example is a two-path correction method using leftand upper neighboring blocks, it is to be noted that the correctionmethod may be three- or more-path correction method using also the rightneighboring block and/or the lower neighboring block.

It is to be noted that the region in which such overlapping is performedmay be only part of a region near a block boundary instead of the pixelregion of the entire block.

It is to be noted that the prediction image correction process accordingto OBMC for obtaining one prediction image Pred from one referencepicture by overlapping additional prediction image Pred_L and Pred_Uhave been described above. However, when a prediction image is correctedbased on a plurality of reference images, a similar process may beapplied to each of the plurality of reference pictures. In such a case,after corrected prediction images are obtained from the respectivereference pictures by performing OBMC image correction based on theplurality of reference pictures, the obtained corrected predictionimages are further overlapped to obtain the final prediction image.

It is to be noted that, in OBMC, the unit of a current block may be theunit of a prediction block or the unit of a sub-block obtained byfurther splitting the prediction block.

One example of a method for determining whether to apply an OBMC processis a method for using an obmc_flag which is a signal indicating whetherto apply an OBMC process. As one specific example, an encoder determineswhether the current block belongs to a region having complicated motion.The encoder sets the obmc_flag to a value of “1” when the block belongsto a region having complicated motion and applies an OBMC process whenencoding, and sets the obmc_flag to a value of “0” when the block doesnot belong to a region having complicated motion and encodes the blockwithout applying an OBMC process. The decoder switches betweenapplication and non-application of an OBMC process by decoding theobmc_flag written in the stream (for example, a compressed sequence) anddecoding the block by switching between the application andnon-application of the OBMC process in accordance with the flag value.

Inter predictor 126 generates one rectangular prediction image for arectangular current block in the above example. However, inter predictor126 may generate a plurality of prediction images each having a shapedifferent from a rectangle for the rectangular current block, and maycombine the plurality of prediction images to generate the finalrectangular prediction image. The shape different from a rectangle maybe, for example, a triangle.

FIG. 37 is a conceptual diagram for illustrating generation of twotriangular prediction images.

Inter predictor 126 generates a triangular prediction image byperforming motion compensation of a first partition having a triangularshape in a current block by using a first MV of the first partition, togenerate a triangular prediction image. Likewise, inter predictor 126generates a triangular prediction image by performing motioncompensation of a second partition having a triangular shape in acurrent block by using a second MV of the second partition, to generatea triangular prediction image. Inter predictor 126 then generates aprediction image having the same rectangular shape as the rectangularshape of the current block by combining these prediction images.

It is to be noted that, although the first partition and the secondpartition are triangles in the example illustrated in FIG. 37, the firstpartition and the second partition may be trapezoids, or other shapesdifferent from each other. Furthermore, although the current blockincludes two partitions in the example illustrated in FIG. 37, thecurrent block may include three or more partitions.

In addition, the first partition and the second partition may overlapwith each other. In other words, the first partition and the secondpartition may include the same pixel region. In this case, a predictionimage for a current block may be generated using a prediction image inthe first partition and a prediction image in the second partition.

In addition, although an example in which a prediction image isgenerated for each of two partitions using inter prediction, aprediction image may be generated for at least one partition using intraprediction.

[Motion Compensation>BIO]

Next, a method for deriving a motion vector is described. First, a modefor deriving a motion vector based on a model assuming uniform linearmotion will be described. This mode is also referred to as abi-directional optical flow (BIO) mode.

FIG. 38 is a conceptual diagram for illustrating a model assuminguniform linear motion. In FIG. 38, (vx, vy) indicates a velocity vector,and τ0 and τ1 indicate temporal distances between a current picture (CurPic) and two reference pictures (Ref0, Ref1). (MVx0, MVy0) indicatemotion vectors corresponding to reference picture Ref0, and (MVx1, MVy1)indicate motion vectors corresponding to reference picture Ref1.

Here, under the assumption of uniform linear motion exhibited byvelocity vectors (vx, vy), (MVx0, MVy0) and (MVx1, MVy1) are representedas (vxτ0, vyτ0) and (−vxτ1, −vyτ1), respectively, and the followingoptical flow equation (2) may be employed.[MATH. 3]∂I ^((k)) /∂t+v _(x) ∂I ^((k)) /∂x+v _(y) ∂I ^((k)) /∂y=0.  (2)

Here, I(k) indicates a motion-compensated luma value of referencepicture k (k=0, 1). This optical flow equation shows that the sum of (i)the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference image, and (iii) the product of the vertical velocity andthe vertical component of the spatial gradient of a reference image isequal to zero. A motion vector of each block obtained from, for example,a merge list may be corrected in units of a pixel, based on acombination of the optical flow equation and Hermite interpolation.

It is to be noted that a motion vector may be derived on the decoderside using a method other than deriving a motion vector based on a modelassuming uniform linear motion. For example, a motion vector may bederived in units of a sub-block based on motion vectors of neighboringblocks.

[Motion Compensation>LIC]

Next, an example of a mode in which a prediction image (prediction) isgenerated by using a local illumination compensation (LIC) process willbe described.

FIG. 39 is a conceptual diagram for illustrating one example of aprediction image generation method using a luminance correction processperformed by a LIC process.

First, an MV is derived from an encoded reference picture, and areference image corresponding to the current block is obtained.

Next, information indicating how the luma value changed between thereference picture and the current picture is extracted for the currentblock. This extraction is performed based on the luma pixel values forthe encoded left neighboring reference region (surrounding referenceregion) and the encoded upper neighboring reference region (surroundingreference region), and the luma pixel value at the correspondingposition in the reference picture specified by the derived MV. Aluminance correction parameter is calculated by using the informationindicating how the luma value changed.

The prediction image for the current block is generated by performing aluminance correction process in which the luminance correction parameteris applied to the reference image in the reference picture specified bythe MV.

It is to be noted that the shape of the surrounding reference regionillustrated in FIG. 39 is just one example; the surrounding referenceregion may have a different shape.

Moreover, although the process in which a prediction image is generatedfrom a single reference picture has been described here, cases in whicha prediction image is generated from a plurality of reference picturescan be described in the same manner. The prediction image may begenerated after performing a luminance correction process of thereference images obtained from the reference pictures in the same manneras described above.

One example of a method for determining whether to apply a LIC processis a method for using a lic_flag which is a signal indicating whether toapply the LIC process. As one specific example, the encoder determineswhether the current block belongs to a region having a luminance change.The encoder sets the lic_flag to a value of “1” when the block belongsto a region having a luminance change and applies a LIC process whenencoding, and sets the lic_flag to a value of “0” when the block doesnot belong to a region having a luminance change and encodes the currentblock without applying a LIC process. The decoder may decode thelic_flag written in the stream and decode the current block by switchingbetween application and non-application of a LIC process in accordancewith the flag value.

One example of a different method of determining whether to apply a LICprocess is a determining method in accordance with whether a LIC processwas applied to a surrounding block. In one specific example, when themerge mode is used on the current block, whether a LIC process wasapplied in the encoding of the surrounding encoded block selected uponderiving the MV in the merge mode process is determined. According tothe result, encoding is performed by switching between application andnon-application of a LIC process. It is to be noted that, also in thisexample, the same processes are applied in processes at the decoderside.

An embodiment of the luminance correction (LIC) process described withreference to FIG. 39 is described in detail below.

First, inter predictor 126 derives a motion vector for obtaining areference image corresponding to a current block to be encoded from areference picture which is an encoded picture.

Next, inter predictor 126 extracts information indicating how the lumavalue of the reference picture has been changed to the luma value of thecurrent picture, using the luma pixel value of an encoded surroundingreference region which neighbors to the left of or above the currentblock and the luma value in the corresponding position in the referencepicture specified by a motion vector, and calculates a luminancecorrection parameter. For example, it is assumed that the luma pixelvalue of a given pixel in the surrounding reference region in thecurrent picture is p0, and that the luma pixel value of the pixelcorresponding to the given pixel in the surrounding reference region inthe reference picture is p1. Inter predictor 126 calculates coefficientsA and B for optimizing A×p1+B=p0 as the luminance correction parameterfor a plurality of pixels in the surrounding reference region.

Next, inter predictor 126 performs a luminance correction process usingthe luminance correction parameter for the reference image in thereference picture specified by the motion vector, to generate aprediction image for the current block. For example, it is assumed thatthe luma pixel value in the reference image is p2, and that theluminance-corrected luma pixel value of the prediction image is p3.Inter predictor 126 generates the prediction image after being subjectedto the luminance correction process by calculating A×p2+B=p3 for each ofthe pixels in the reference image.

It is to be noted that the shape of the surrounding reference regionillustrated in FIG. 39 is one example; a different shape other than theshape of the surrounding reference region may be used. In addition, partof the surrounding reference region illustrated in FIG. 39 may be used.For example, a region having a determined number of pixels extractedfrom each of an upper neighboring pixel and a left neighboring pixel maybe used as a surrounding reference region. The determined number ofpixels may be predetermined.

In addition, the surrounding reference region is not limited to a regionwhich neighbors the current block, and may be a region which does notneighbor the current block. In the example illustrated in FIG. 39, thesurrounding reference region in the reference picture is a regionspecified by a motion vector in a current picture, from a surroundingreference region in the current picture. However, a region specified byanother motion vector is also possible. For example, the other motionvector may be a motion vector in a surrounding reference region in thecurrent picture.

Although operations performed by encoder 100 have been described here,it is to be noted that decoder 200 typically performs similaroperations.

It is to be noted that the LIC process may be applied not only to theluma but also to chroma. At this time, a correction parameter may bederived individually for each of Y, Cb, and Cr, or a common correctionparameter may be used for any of Y, Cb, and Cr.

In addition, the LIC process may be applied in units of a sub-block. Forexample, a correction parameter may be derived using a surroundingreference region in a current sub-block and a surrounding referenceregion in a reference sub-block in a reference picture specified by anMV of the current sub-block.

[Prediction Controller]

Inter predictor 128 selects one of an intra prediction signal (a signaloutput from intra predictor 124) and an inter prediction signal (asignal output from inter predictor 126), and outputs the selected signalto subtractor 104 and adder 116 as a prediction signal.

As illustrated in FIG. 1, in various kinds of encoder examples,prediction controller 128 may output a prediction parameter which isinput to entropy encoder 110. Entropy encoder 110 may generate anencoded bitstream (or a sequence), based on the prediction parameterwhich is input from prediction controller 128 and quantized coefficientswhich are input from quantizer 108. The prediction parameter may be usedin a decoder. The decoder may receive and decode the encoded bitstream,and perform the same processes as the prediction processes performed byintra predictor 124, inter predictor 126, and prediction controller 128.The prediction parameter may include (i) a selection prediction signal(for example, a motion vector, a prediction type, or a prediction modeused by intra predictor 124 or inter predictor 126), or (ii) an optionalindex, a flag, or a value which is based on a prediction processperformed in each of intra predictor 124, inter predictor 126, andprediction controller 128, or which indicates the prediction process.

[Mounting Example of Encoder]

FIG. 40 is a block diagram illustrating a mounting example of an encoder100. Encoder 100 includes processor a1 and memory a2. For example, theplurality of constituent elements of encoder 100 illustrated in FIG. 1are mounted on processor a1 and memory a2 illustrated in FIG. 40.

Processor a1 is circuitry which performs information processing and isaccessible to memory a2. For example, processor a1 is dedicated orgeneral electronic circuitry which encodes a video. Processor a1 may bea processor such as a CPU. In addition, processor a1 may be an aggregateof a plurality of electronic circuits. In addition, for example,processor a1 may take the roles of two or more constituent elements outof the plurality of constituent elements of encoder 100 illustrated inFIG. 1, etc.

Memory a2 is dedicated or general memory for storing information that isused by processor a1 to encode a video. Memory a2 may be electroniccircuitry, and may be connected to processor a1. In addition, memory a2may be included in processor a1. In addition, memory a2 may be anaggregate of a plurality of electronic circuits. In addition, memory a2may be a magnetic disc, an optical disc, or the like, or may berepresented as a storage, a recording medium, or the like. In addition,memory a2 may be non-volatile memory, or volatile memory.

For example, memory a2 may store a video to be encoded or a bitstreamcorresponding to an encoded video. In addition, memory a2 may store aprogram for causing processor a1 to encode a video.

In addition, for example, memory a2 may take the roles of two or moreconstituent elements for storing information out of the plurality ofconstituent elements of encoder 100 illustrated in FIG. 1, etc. Forexample, memory a2 may take the roles of block memory 118 and framememory 122 illustrated in FIG. 1. More specifically, memory a2 may storea reconstructed block, a reconstructed picture, etc.

It is to be noted that, in encoder 100, all of the plurality ofconstituent elements indicated in FIG. 1, etc. may not be implemented,and all the processes described above may not be performed. Part of theconstituent elements indicated in FIG. 1, etc. may be included inanother device, or part of the processes described above may beperformed by another device.

[Decoder]

Next, a decoder capable of decoding an encoded signal (encodedbitstream) output, for example, from encoder 100 described above will bedescribed. FIG. 41 is a block diagram illustrating a functionalconfiguration of decoder 200 according to an embodiment. Decoder 200 isa video decoder which decodes a video in units of a block.

As illustrated in FIG. 41, decoder 200 includes entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, block memory210, loop filter 212, frame memory 214, intra predictor 216, interpredictor 218, and prediction controller 220.

Decoder 200 is implemented as, for example, a generic processor andmemory. In this case, when a software program stored in the memory isexecuted by the processor, the processor functions as entropy decoder202, inverse quantizer 204, inverse transformer 206, adder 208, loopfilter 212, intra predictor 216, inter predictor 218, and predictioncontroller 220. Alternatively, decoder 200 may be implemented as one ormore dedicated electronic circuits corresponding to entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, loop filter212, intra predictor 216, inter predictor 218, and prediction controller220.

Hereinafter, an overall flow of processes performed by decoder 200 isdescribed, and then each of constituent elements included in decoder 200will be described.

[Overall Flow of Decoding Process]

FIG. 42 is a flow chart illustrating one example of an overall decodingprocess performed by decoder 200.

First, entropy decoder 202 of decoder 200 identifies a splitting patternof a block having a fixed size (for example, 128×128 pixels) (StepSp_1). This splitting pattern is a splitting pattern selected by encoder100. Decoder 200 then performs processes of Step Sp_2 to Sp_6 for eachof a plurality of blocks of the splitting pattern.

In other words, entropy decoder 202 decodes (specifically,entropy-decodes) encoded quantized coefficients and a predictionparameter of a current block to be decoded (also referred to as acurrent block) (Step Sp_2).

Next, inverse quantizer 204 performs inverse quantization of theplurality of quantized coefficients and inverse transformer 206 performsinverse transform of the result, to restore a plurality of predictionresiduals (that is, a difference block) (Step Sp_3).

Next, the prediction processor including all or part of intra predictor216, inter predictor 218, and prediction controller 220 generates aprediction signal (also referred to as a prediction block) of thecurrent block (Step Sp_4).

Next, adder 208 adds the prediction block to the difference block togenerate a reconstructed image (also referred to as a decoded imageblock) of the current block (Step Sp_5).

When the reconstructed image is generated, loop filter 212 performsfiltering of the reconstructed image (Step Sp_6).

Decoder 200 then determines whether decoding of the entire picture hasbeen finished (Step Sp_7). When determining that the decoding has notyet been finished (No in Step Sp_7), decoder 200 repeatedly executes theprocesses starting with Step Sp_1.

As illustrated, the processes of Steps Sp_1 to Sp_7 are performedsequentially by decoder 200, Alternatively, two or more of the processesmay be performed in parallel, the processing order of the two or more ofthe processes may be modified, etc.

[Entropy Decoder]

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204. Entropydecoder 202 may output a prediction parameter included in an encodedbitstream (see FIG. 1) to intra predictor 216, inter predictor 218, andprediction controller 220. Intra predictor 216, inter predictor 218, andprediction controller 220 in an embodiment are capable of executing thesame prediction processes as those performed by intra predictor 124,inter predictor 126, and prediction controller 128 at the encoder side.

[Inverse Quantizer]

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block) whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock, based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedtransform coefficients of the current block to inverse transformer 206.

[Inverse Transformer]

Inverse transformer 206 restores prediction errors by inversetransforming the transform coefficients which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesthat EMT or AMT is to be applied (for example, when an AMT flag istrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type.

Moreover, for example, when information parsed from an encoded bitstreamindicates that NSST is to be applied, inverse transformer 206 applies asecondary inverse transform to the transform coefficients.

[Adder]

Adder 208 reconstructs the current block by adding prediction errorswhich are inputs from inverse transformer 206 and prediction sampleswhich are inputs from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

[Block Memory]

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) and to bereferred to in intra prediction. More specifically, block memory 210stores reconstructed blocks output from adder 208.

[Loop Filter]

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214,display device, etc.

When information indicating ON or OFF of an ALF parsed from an encodedbitstream indicates that an ALF is ON, one filter from among a pluralityof filters is selected based on direction and activity of localgradients, and the selected filter is applied to the reconstructedblock.

[Frame Memory]

Frame memory 214 is, for example, storage for storing reference picturesfor use in inter prediction, and is also referred to as a frame buffer.More specifically, frame memory 214 stores a reconstructed blockfiltered by loop filter 212.

[Prediction Processor (Intra Predictor, Inter Predictor, PredictionController)]

FIG. 43 is a flow chart illustrating one example of a process performedby a prediction processor of decoder 200. It is to be noted that theprediction processor includes all or part of the following constituentelements: intra predictor 216; inter predictor 218; and predictioncontroller 220.

The prediction processor generates a prediction image of a current block(Step Sq_1). This prediction image is also referred to as a predictionsignal or a prediction block. It is to be noted that the predictionsignal is, for example, an intra prediction signal or an interprediction signal. Specifically, the prediction processor generates theprediction image of the current block using a reconstructed image whichhas been already obtained through generation of a prediction block,generation of a difference block, generation of a coefficient block,restoring of a difference block, and generation of a decoded imageblock.

The reconstructed image may be, for example, an image in a referencepicture, or an image of a decoded block in a current picture which isthe picture including the current block. The decoded block in thecurrent picture is, for example, a neighboring block of the currentblock.

FIG. 44 is a flow chart illustrating another example of a processperformed by the prediction processor of decoder 200.

The prediction processor determines either a method or a mode forgenerating a prediction image (Step Sr_1). For example, the method ormode may be determined based on, for example, a prediction parameter,etc.

When determining a first method as a mode for generating a predictionimage, the prediction processor generates a prediction image accordingto the first method (Step Sr_2 a). When determining a second method as amode for generating a prediction image, the prediction processorgenerates a prediction image according to the second method (Step Sr_2b). When determining a third method as a mode for generating aprediction image, the prediction processor generates a prediction imageaccording to the third method (Step Sr_2 c).

The first method, the second method, and the third method may bemutually different methods for generating a prediction image. Each ofthe first to third methods may be an inter prediction method, an intraprediction method, or another prediction method. The above-describedreconstructed image may be used in these prediction methods.

[Intra Predictor]

Intra predictor 216 generates a prediction signal (intra predictionsignal) by performing intra prediction by referring to a block or blocksin the current picture stored in block memory 210, based on the intraprediction mode parsed from the encoded bitstream. More specifically,intra predictor 216 generates an intra prediction signal by performingintra prediction by referring to samples (for example, luma and/orchroma values) of a block or blocks neighboring the current block, andthen outputs the intra prediction signal to prediction controller 220.

It is to be noted that when an intra prediction mode in which a lumablock is referred to in intra prediction of a chroma block is selected,intra predictor 216 may predict the chroma component of the currentblock based on the luma component of the current block.

Moreover, when information parsed from an encoded bitstream indicatesthat PDPC is to be applied, intra predictor 216 corrects intra-predictedpixel values based on horizontal/vertical reference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block by referring to areference picture stored in frame memory 214. Inter prediction isperformed in units of a current block or a sub-block (for example, a 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or the sub-block byperforming motion compensation by using motion information (for example,a motion vector) parsed from an encoded bitstream (for example, aprediction parameter output from entropy decoder 202), and outputs theinter prediction signal to prediction controller 220.

It is to be noted that when the information parsed from the encodedbitstream indicates that the OBMC mode is to be applied, inter predictor218 generates the inter prediction signal using motion information of aneighboring block in addition to motion information of the current blockobtained from motion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates that the FRUC mode is to be applied, inter predictor 218derives motion information by performing motion estimation in accordancewith the pattern matching method (bilateral matching or templatematching) parsed from the encoded bitstream. Inter predictor 218 thenperforms motion compensation (prediction) using the derived motioninformation.

Moreover, when the BIO mode is to be applied, inter predictor 218derives a motion vector based on a model assuming uniform linear motion.Moreover, when the information parsed from the encoded bitstreamindicates that the affine motion compensation prediction mode is to beapplied, inter predictor 218 derives a motion vector of each sub-blockbased on motion vectors of neighboring blocks.

[MV Derivation>Normal Inter Mode]

When information parsed from an encoded bitstream indicates that thenormal inter mode is to be applied, inter predictor 218 derives an MVbased on the information parsed from the encoded bitstream and performsmotion compensation (prediction) using the MV.

FIG. 45 is a flow chart illustrating an example of inter prediction innormal inter mode in decoder 200.

Inter predictor 218 of decoder 200 performs motion compensation for eachblocks. Inter predictor 218 obtains a plurality of MV candidates for acurrent block based on information such as MVs of a plurality of decodedblocks temporally or spatially surrounding the current block (StepSs_1). In other words, inter predictor 218 generates an MV candidatelist.

Next, inter predictor 218 extracts N (an integer of 2 or larger) MVcandidates from the plurality of MV candidates obtained in Step Ss_1, asmotion vector predictor candidates (also referred to as MV predictorcandidates) according to a determined priority order (Step Ss_2). It isto be noted that the priority order may be determined in advance foreach of the N MV predictor candidates.

Next, inter predictor 218 decodes motion vector predictor selectioninformation from an input stream (that is, an encoded bitstream), andselects, one MV predictor candidate from the N MV predictor candidatesusing the decoded motion vector predictor selection information, as amotion vector (also referred to as an MV predictor) of the current block(Step Ss_3).

Next, inter predictor 218 decodes an MV difference from the inputstream, and derives an MV for a current block by adding a differencevalue which is the decoded MV difference and a selected motion vectorpredictor (Step Ss_4).

Lastly, inter predictor 218 generates a prediction image for the currentblock by performing motion compensation of the current block using thederived MV and the decoded reference picture (Step Ss_5).

[Prediction Controller]

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208. As a whole, the configurations, functions, and processesof prediction controller 220, intra predictor 216, and inter predictor218 at the decoder side may correspond to the configurations, functions,and processes of prediction controller 128, intra predictor 124, andinter predictor 126 at the encoder side.

[Mounting Example of Decoder]

FIG. 46 is a block diagram illustrating a mounting example of a decoder200. Decoder 200 includes processor b1 and memory b2. For example, theplurality of constituent elements of decoder 200 illustrated in FIG. 41are mounted on processor b1 and memory b2 illustrated in FIG. 46.

Processor b1 is circuitry which performs information processing and isaccessible to memory b2. For example, processor b1 is dedicated orgeneral electronic circuitry which decodes a video (that is, an encodedbitstream). Processor b1 may be a processor such as a CPU. In addition,processor b1 may be an aggregate of a plurality of electronic circuits.In addition, for example, processor b1 may take the roles of two or moreconstituent elements out of the plurality of constituent elements ofdecoder 200 illustrated in FIG. 41, etc.

Memory b2 is dedicated or general memory for storing information that isused by processor b1 to decode an encoded bitstream. Memory b2 may beelectronic circuitry, and may be connected to processor b1. In addition,memory b2 may be included in processor b1. In addition, memory b2 may bean aggregate of a plurality of electronic circuits. In addition, memoryb2 may be a magnetic disc, an optical disc, or the like, or may berepresented as a storage, a recording medium, or the like. In addition,memory b2 may be a non-volatile memory, or a volatile memory.

For example, memory b2 may store a video or a bitstream. In addition,memory b2 may store a program for causing processor b1 to decode anencoded bitstream.

In addition, for example, memory b2 may take the roles of two or moreconstituent elements for storing information out of the plurality ofconstituent elements of decoder 200 illustrated in FIG. 41, etc.Specifically, memory b2 may take the roles of block memory 210 and framememory 214 illustrated in FIG. 41. More specifically, memory b2 maystore a reconstructed block, a reconstructed picture, etc.

It is to be noted that, in decoder 200, all of the plurality ofconstituent elements illustrated in FIG. 41, etc. may not beimplemented, and all the processes described above may not be performed.Part of the constituent elements indicated in FIG. 41, etc. may beincluded in another device, or part of the processes described above maybe performed by another device.

[Definitions of Terms]

The respective terms may be defined as indicated below as examples.

A picture is an array of luma samples in monochrome format or an arrayof luma samples and two corresponding arrays of chroma samples in 4:2:0,4:2:2, and 4:4:4 color format. A picture may be either a frame or afield.

A frame is the composition of a top field and a bottom field, wheresample rows 0, 2, 4, . . . originate from the top field and sample rows1, 3, 5, . . . originate from the bottom field.

A slice is an integer number of coding tree units contained in oneindependent slice segment and all subsequent dependent slice segments(if any) that precede the next independent slice segment (if any) withinthe same access unit.

A tile is a rectangular region of coding tree blocks within a particulartile column and a particular tile row in a picture. A tile may be arectangular region of the frame that is intended to be able to bedecoded and encoded independently, although loop-filtering across tileedges may still be applied.

A block is an M×N (M-column by N-row) array of samples, or an M×N arrayof transform coefficients. A block may be a square or rectangular regionof pixels including one Luma and two Chroma matrices.

A coding tree unit (CTU) may be a coding tree block of luma samples of apicture that has three sample arrays, or two corresponding coding treeblocks of chroma samples. Alternatively, a CTU may be a coding treeblock of samples of one of a monochrome picture and a picture that iscoded using three separate color planes and syntax structures used tocode the samples. A super block may be a square block of 64×64 pixelsthat consists of either 1 or 2 mode info blocks or is recursivelypartitioned into four 32×32 blocks, which themselves can be furtherpartitioned.

FIG. 47 is a flow chart illustrating one example of a process ofsplitting an image block into partitions including at least a firstpartition having a non-rectangular shape (e.g., a triangle) and a secondpartition, and performing further processing including encoding (ordecoding) the image block as a reconstructed combination of the firstand second partitions.

In step S1001, an image block is split into partitions including a firstpartition having a non-rectangular shape and a second partition, whichmay or may not have a non-rectangular shape. For example, as shown inFIG. 48, an image block may be split from a top-left corner of the imageblock to a bottom-right corner of the image block to create a firstpartition and a second partition both having a non-rectangular shape(e.g., a triangle), or an image block may be split from a top-rightcorner of the image block to a bottom-left corner of the image block tocreate a first partition and a second partition both having anon-rectangular shape (e.g., a triangle). Various examples of thenon-rectangular partitioning will be described below in reference toFIGS. 48 and 53-55.

In step S1002, the process predicts a first motion vector for the firstpartition and predicts a second motion vector for the second partition.For example, the predicting of the first and second motion vectors mayinclude selecting the first motion vector from a first set of motionvector candidates and selecting the second motion vector from a secondset of motion vector candidates.

In step S1003, a motion compensation process is performed to obtain thefirst partition using the first motion vector, which is derived in stepS1002 above, and to obtain the second partition using the second motionvector, which is derived in step S1002 above.

In step S1004, a prediction process is performed for the image block asa (reconstructed) combination of the first partition and the secondpartition. The prediction process may include a boundary smoothingprocess to smooth out the boundary between the first partition and thesecond partition. For example, the boundary smoothing process mayinvolve weighting first values of boundary pixels predicted based on thefirst partition and second values of the boundary pixels predicted basedon the second partition. Various implementations of the boundarysmoothing process will be described below in reference to FIGS. 49, 50,56 and 57A-57D.

In step S1005, the process encodes or decodes the image block using oneor more parameters including a partition parameter indicative of thesplitting of the image block into the first partition having anon-rectangular shape and the second partition. As summarized in a tableof FIG. 51, for example, the partition parameter (“the first indexvalue”) may jointly encode, for example, a split direction applied inthe splitting (e.g., from top-left to bottom-right or from top-right tobottom-left as shown in FIG. 48) and the first and second motion vectorsderived in step S1002 above. Details of such partition syntax operationinvolving the one or more parameters including the partition parameterwill be described in detail below in reference to FIGS. 51, 52 and58-61.

FIG. 53 is a flowchart illustrating a process 2000 of splitting an imageblock. In step S2001, the process splits an image into a plurality ofpartitions including a first partition having a non-rectangular shapeand a second partition, which may or may not have a non-rectangularshape. As shown in FIG. 48, an image block may be split into a firstpartition having a triangle shape and a second partition also having atriangle shape. There are numerous other examples in which an imageblock is split into a plurality of partitions including a firstpartition and a second partition of which at least the first partitionhas a non-rectangular shape. The non-rectangular shape may be atriangle, a trapezoid, and a polygon with at least five sides andangles.

For example, as shown in FIG. 54, an image block may be split into twotriangular shape partitions; an image block may be split into more thantwo triangular shape partitions (e.g., three triangular shapepartitions); an image block may be split into a combination oftriangular shape partition(s) and rectangular shape partition(s); or animage block may be split into a combination of triangle shapepartition(s) and polygon shape partition(s).

As further shown in FIG. 55, an image block may be split into anL-shaped (polygon shape) partition and a rectangular shape partition; animage block may be split into a pentagon (polygon) shape partition and atriangular shape partition; an image block may be split into a hexagon(polygon) shape partition and a pentagon (polygon) shape partition; oran image block may be split into multiple polygon shape partitions.

Referring back to FIG. 53, in step S2002, the process predicts a firstmotion vector for the first partition, for example by selecting thefirst partition from a first set of motion vector candidates, andpredicts a second motion vector for the second partition, for example byselecting the second partition from a second set of motion vectorcandidates. For example, the first set of motion vector candidates mayinclude motion vectors of partitions neighboring the first partition,and the second set of motion vector candidates may include motionvectors of partitions neighboring the second partition. The neighboringpartitions may be one or both of spatially neighboring partitions andtemporary neighboring partitions. Some examples of the spatiallyneighboring partitions include a partition located at the left,bottom-left, bottom, bottom-right, right, top-right, top, or top-left ofthe partition that is being processed. Examples of the temporaryneighboring partitions are co-located partitions in the referencepictures of the image block.

In various implementations, the partitions neighboring the firstpartition and the partitions neighboring the second partition may beoutside of the image block from which the first partition and the secondpartition are split. The first set of motion vector candidates may bethe same as, or different from, the second set of motion vectorcandidates. Further, at least one of the first set of motion vectorcandidates and the second set of motion vector candidates may be thesame as another, third set of motion vector candidates prepared for theimage block.

In some implementations, in step S2002, in response to determining thatthe second partition, similar to the first partition, too has anon-rectangular shape (e.g., a triangle), the process 2000 creates thesecond set of motion vector candidates (for the non-rectangular shapesecond partition) that includes motion vectors of partitions neighboringthe second partition exclusive of the first partition (exclusive of themotion vector of the first partition). On the other hand, in response todetermining that the second partition, unlike the first partition, has arectangular shape, the process 2000 creates the second set of motionvector candidates (for the rectangular shape second partition) thatincludes motion vectors of partitions neighboring the second partitioninclusive of the first partition.

In step S2003, the process encodes or decodes the first partition usingthe first motion vector derived in step S2002 above, and encodes ordecodes the second partition using the second motion vector derived instep S2002 above.

An image block splitting process, like the process 2000 of FIG. 53, maybe performed by an image encoder, as shown in FIG. 1 for example, whichincludes circuitry and a memory coupled to the circuitry. The circuitry,in operation, performs: splitting an image block into a plurality ofpartitions including a first partition having a non-rectangular shapeand a second partition (step S2001); predicting a first motion vectorfor the first partition and a second motion vector for the secondpartition (step S2002); and encoding the first partition using the firstmotion vector and the second partition using the second motion vector(step S2003).

According to another embodiment, as shown in FIG. 1, an image encoder isprovided including: a splitter 102 which, in operation, receives andsplits an original picture into blocks; an adder 104 which, inoperation, receives the blocks from the splitter and predictions from aprediction controller 128, and subtracts each prediction from itscorresponding block to output a residual; a transformer 106 which, inoperation, performs a transform on the residuals outputted from theadder 104 to output transform coefficients; a quantizer 108 which, inoperation, quantizes the transform coefficients to generate quantizedtransform coefficients; an entropy encoder 110 which, in operation,encodes the quantized transform coefficients to generate a bitstream;and the prediction controller 128 coupled to an inter predictor 126, anintra predictor 124, and a memory 118, 122, wherein the inter predictor126, in operation, generates a prediction of a current block based on areference block in an encoded reference picture and the intra predictor124, in operation, generates a prediction of a current block based on anencoded reference block in a current picture. The prediction controller128, in operation, splits the blocks into a plurality of partitionsincluding a first partition having a non-rectangular shape and a secondpartition (FIG. 53, step S2001); predicts a first motion vector for thefirst partition and a second motion vector for the second partition(step S2002); and encodes the first partition using the first motionvector and the second partition using the second motion vector (stepS2003).

According to another embodiment, an image decoder, as shown in FIG. 41for example, is provided which includes circuitry and a memory coupledto the circuitry. The circuitry, in operation, performs: splitting animage block into a plurality of partitions including a first partitionhaving a non-rectangular shape and a second partition (FIG. 53, stepS2001); predicting a first motion vector for the first partition and asecond motion vector for the second partition (step S2002); and decodingthe first partition using the first motion vector and the secondpartition using the second motion vector (step S2003).

According to a further embodiment, an image decoder as shown in FIG. 41is provided including: an entropy decoder 202 which, in operation,receives and decodes an encoded bitstream to obtain quantized transformcoefficients; an inverse quantizer 204 and transformer 206 which, inoperation, inverse quantizes the quantized transform coefficients toobtain transform coefficients and inverse transform the transformcoefficients to obtain residuals; an adder 208 which, in operation, addsthe residuals outputted from the inverse quantizer 204 and transformer206 and predictions outputted from a prediction controller 220 toreconstruct blocks; and the prediction controller 220 coupled to aninter predictor 218, an intra predictor 216, and a memory 210, 214,wherein the inter predictor 218, in operation, generates a prediction ofa current block based on a reference block in a decoded referencepicture and the intra predictor 216, in operation, generates aprediction of a current block based on an decoded reference block in acurrent picture. The prediction controller 220, in operation, splits animage block into a plurality of partitions including a first partitionhaving a non-rectangular shape and a second partition (FIG. 53, stepS2001); predicts a first motion vector for the first partition and asecond motion vector for the second partition (step S2002); and decodesthe first partition using the first motion vector and the secondpartition using the second motion vector (step S2003).

(Boundary Smoothing)

As described above in FIG. 47, step S1004, according to variousembodiments, performing a prediction process for the image block as a(reconstructed) combination of the first partition having anon-rectangular shape and the second partition may involve applicationof a boundary smoothing process along the boundary between the firstpartition and the second partition.

For example, FIG. 57B illustrates one example of a boundary smoothingprocess involving weighting first values of boundary pixels, which arefirst-predicted based on the first partition, and second values of theboundary pixels, which are second-predicted based on the secondpartition.

FIG. 56 is a flowchart illustrating an overall boundary smoothingprocess 3000 involving weighting first values of boundary pixelsfirst-predicted based on the first partition and second values of theboundary pixels second-predicted based on the second partition,according to one embodiment. In step S3001, an image block is split intoa first partition and a second partition along a boundary wherein atleast the first partition has a non-rectangular shape, as shown in FIG.57A or in FIGS. 48, 54 and 55 described above.

In step S3002, first values (e.g., color, luminance, transparency, etc.)of a set of pixels (“boundary pixels” in FIG. 57A) of the firstpartition along the boundary are first-predicted, wherein the firstvalues are first-predicted using information of the first partition. Instep S3003, second values of the (same) set of pixels of the firstpartition along the boundary are second-predicted, wherein the secondvalues are second-predicted using information of the second partition.In some implementation, at least one of the first-predicting and thesecond-predicting is an inter prediction process that predicts the firstvalues and the second values based on a reference partition in anencoded reference picture. Referring to FIG. 57D, in someimplementations, the prediction process predicts first values of allpixels of the first partition (“the first set of samples”) including theset of pixels over which the first partition and the second partitionoverlap, and predicts second values of only the set of pixels (“thesecond set of samples”) over which the first and second partitionsoverlap. In another implementation, at least one of the first-predictingand the second-predicting is an intra prediction process that predictsthe first values and the second values based on an encoded referencepartition in a current picture. In some implementations, a predictionmethod used in the first-predicting is different from a predictionmethod used in the second-predicting. For example, the first-predictingmay include an inter prediction process and the second-predicting mayinclude an intra prediction process. The information used tofirst-predict the first values or to second-predict the second valuesmay be motion vectors, intra-prediction directions, etc. of the first orsecond partition.

In step S3004, the first values, predicted using the first partition,and the second values, predicted using the second partition, areweighted. In step S3005, the first partition is encoded or decoded usingthe weighted first and second values.

FIG. 57B illustrates an example of a boundary smoothing operationwherein the first partition and the second partition overlap over fivepixels (at a maximum) of each row or each column. That is, the number ofthe set of pixels of each row or each column, for which the first valuesare predicted based on the first partition and the second values arepredicted based on the second partition, are five at a maximum. FIG. 57Cillustrates another example of a boundary smoothing operation whereinthe first partition and the second partition overlap over three pixels(at a maximum) of each row or each column. That is, the number of theset of pixels of each row or each column, for which the first values arepredicted based on the first partition and the second values arepredicted based on the second partition, are three at a maximum.

FIG. 49 illustrates another example of boundary smoothing operationwherein the first partition and the second partition overlap over fourpixels (at a maximum) of each row or each column. That is, the number ofthe set of pixels of each row or each column, for which the first valuesare predicted based on the first partition and the second values arepredicted based on the second partition, are four at a maximum. In theillustrated example, weights of ⅛, ¼, ¾, and ⅞ may be applied to thefirst values of the four pixels in the set, respectively, and weights of⅞, ¾, ¼, and ⅛ may be applied to the second values of the four pixels inthe set, respectively.

FIG. 50 illustrate further examples of a boundary smoothing operationwherein the first partition and the second partition overlap over zeropixels of each row or each column (they do not overlap), overlap overone pixel (at a maximum) of each row or each column, and overlap overtwo pixels (at a maximum) of each row or each column, respectively. Inthe example wherein the first and second partitions do not overlap, zeroweights are applied. In the example wherein the first and secondpartitions overlap over one pixel of each row or each column, a weightof ½ may be applied to the first values of the pixels in the setpredicted based on the first partition, and a weight of ½ may be appliedto the second values of the pixels in the set predicted based on thesecond partition. In the example wherein the first and second partitionsoverlap over two pixels of each row or each column, weights of ⅓ and ⅔may be applied to the first values of the two pixels in the setpredicted based on the first partition, respectively, and weights of ⅔and ⅓ may be applied to the second values of the two pixels in the setpredicted based on the second partition, respectively.

According to the embodiments described above, the number of pixels inthe set over which the first partition and the second partition overlapis an integer. In other implementations, the number of overlappingpixels in the set may be non-integer and may be fractional, for example.Also, the weights applied to the first and second values of the set ofpixels may be fractional or integer depending on each application.

A boundary smoothing process, like the process 3000 of FIG. 56, may beperformed by an image encoder, as shown in FIG. 1 for example, whichincludes circuitry and a memory coupled to the circuitry. The circuitry,in operation, performs a boundary smoothing operation along a boundarybetween a first partition having a non-rectangular shape and a secondpartition that are split from an image block (FIG. 56, step S3001). Theboundary smoothing operation includes: first-predicting first values ofa set of pixels of the first partition along the boundary, usinginformation of the first partition (step S3002); second-predictingsecond values of the set of pixels of the first partition along theboundary, using information of the second partition (step S3003);weighting the first values and the second values (step S3004); andencoding the first partition using the weighted first values and theweighted second values (step S3005).

According to another embodiment, as shown in FIG. 1, an image encoder isprovided including: a splitter 102 which, in operation, receives andsplits an original picture into blocks; an adder 104 which, inoperation, receives the blocks from the splitter and predictions from aprediction controller 128, and subtracts each prediction from itscorresponding block to output a residual; a transformer 106 which, inoperation, performs a transform on the residuals outputted from theadder 104 to output transform coefficients; a quantizer 108 which, inoperation, quantizes the transform coefficients to generate quantizedtransform coefficients; an entropy encoder 110 which, in operation,encodes the quantized transform coefficients to generate a bitstream;and the prediction controller 128 coupled to an inter predictor 126, anintra predictor 124, and a memory 118, 122, wherein the inter predictor126, in operation, generates a prediction of a current block based on areference block in an encoded reference picture and the intra predictor124, in operation, generates a prediction of a current block based on anencoded reference block in a current picture. The prediction controller128, in operation, performs a boundary smoothing operation along aboundary between a first partition having a non-rectangular shape and asecond partition that are split from an image block (FIG. 56, stepS3001). The boundary smoothing operation includes: first-predictingfirst values of a set of pixels of the first partition along theboundary, using information of the first partition (step S3002);second-predicting second values of the set of pixels of the firstpartition along the boundary, using information of the second partition(step S3003); weighting the first values and the second values (stepS3004); and encoding the first partition using the weighted first valuesand the weighted second values (step S3005).

According to another embodiment, an image decoder is provided, as shownin FIG. 41 for example, which includes circuitry and a memory coupled tothe circuitry. The circuitry, in operation, performs a boundarysmoothing operation along a boundary between a first partition having anon-rectangular shape and a second partition that are split from animage block (FIG. 56, steps S3001). The boundary smoothing operationincludes: first-predicting first values of a set of pixels of the firstpartition along the boundary, using information of the first partition(step S3002); second-predicting second values of the set of pixels ofthe first partition along the boundary, using information of the secondpartition (step S3003); weighting the first values and the second values(step S3004); and decoding the first partition using the weighted firstvalues and the weighted second values (step S3005).

According to another embodiment, an image decoder as shown in FIG. 41 isprovided including: an entropy decoder 202 which, in operation, receivesand decodes an encoded bitstream to obtain quantized transformcoefficients; an inverse quantizer 204 and transformer 206 which, inoperation, inverse quantizes the quantized transform coefficients toobtain transform coefficients and inverse transform the transformcoefficients to obtain residuals; an adder 208 which, in operation, addsthe residuals outputted from the inverse quantizer 204 and transformer206 and predictions outputted from a prediction controller 220 toreconstruct blocks; and the prediction controller 220 coupled to aninter predictor 218, an intra predictor 216, and a memory 210, 214,wherein the inter predictor 218, in operation, generates a prediction ofa current block based on a reference block in a decoded referencepicture and the intra predictor 216, in operation, generates aprediction of a current block based on an decoded reference block in acurrent picture. The prediction controller 220, in operation, performs aboundary smoothing operation along a boundary between a first partitionhaving a non-rectangular shape and a second partition that are splitfrom an image block. (FIG. 56, step S3001) The boundary smoothingoperation includes: first-predicting first values of a set of pixels ofthe first partition along the boundary, using information of the firstpartition (step S3002); second-predicting second values of the set ofpixels of the first partition along the boundary, using information ofthe second partition (step S3003); weighting the first values and thesecond values (step S3004); and decoding the first partition using theweighted first values and the weighted second values (step S3005).

(Entropy Encoding and Decoding Using Partition Parameter Syntax)

As described in FIG. 47, step S1005, according to various embodiments,the image block split into a first partition having a non-rectangularshape and a second partition may be encoded or decoded using one or moreparameters including a partition parameter indicative of thenon-rectangular splitting of the image block. In various embodiments,such partition parameter may jointly encode, for example, a splitdirection applied to the splitting (e.g., from top-left to bottom-rightor from top-right to bottom-left, see FIG. 48) and the first and secondmotion vectors predicted in step S1002, as will be more fully describedbelow.

FIG. 51 is a table of sample partition parameters (“the first indexvalue”) and sets of information jointly encoded by the partitionparameters, respectively. The partition parameters (“the first indexvalues”) range from 0 to 6 and jointly encode: the direction ofsplitting an image block into a first partition and a second partitionboth of which are triangles (see FIG. 48), the first motion vectorpredicted for the first partition (FIG. 47, step S1002), and the secondmotion vector predicted for the second partition (FIG. 47, step S1002).Specifically, the partition parameter 0 encodes the split direction isfrom top-left corner to bottom-right corner, the first motion vector isthe “2nd” motion vector listed in the first set of motion vectorcandidates for the first partition, and the second motion vector is the“1st” motion vector listed in the second set of motion vector candidatesfor the second partition.

The partition parameter 1 encodes the split direction is from top-rightcorner to bottom-left corner, the first motion vector is the “1st”motion vector listed in the first set of motion vector candidates forthe first partition, and the second motion vector is the “2nd” motionvector listed in the second set of motion vector candidates for thesecond partition. The partition parameter 2 encodes the split directionis from top-right corner to bottom-left corner, the first motion vectoris the “2nd” motion vector listed in the first set of motion vectorcandidates for the first partition, and the second motion vector is the“1st” motion vector listed in the second set of motion vector candidatesfor the second partition. The partition parameter 3 encodes the splitdirection is from top-left corner to bottom-right corner, the firstmotion vector is the “2nd” motion vector listed in the first set ofmotion vector candidates for the first partition, and the second motionvector is the “2nd” motion vector listed in the second set of motionvector candidates for the second partition. The partition parameter 4encodes the split direction is from top-right corner to bottom-leftcorner, the first motion vector is the “2nd” motion vector listed in thefirst set of motion vector candidates for the first partition, and thesecond motion vector is the “3rd” motion vector listed in the second setof motion vector candidates for the second partition. The partitionparameter 5 encodes the split direction is from top-left corner tobottom-right corner, the first motion vector is the “3rd” motion vectorlisted in the first set of motion vector candidates for the firstpartition, and the second motion vector is the “1st” motion vectorlisted in the second set of motion vector candidates for the secondpartition. The partition parameter 6 encodes the split direction is fromtop-left corner to bottom-right corner, the first motion vector is the“4th” motion vector listed in the first set of motion vector candidatesfor the first partition, and the second motion vector is the “1st”motion vector listed in the second set of motion vector candidates forthe second partition.

FIG. 58 is a flowchart illustrating a method 4000 performed on theencoder side. In step S4001, the process splits an image block into aplurality of partitions including a first partition having anon-rectangular shape and a second partition, based on a partitionparameter indicative of the splitting. For example, as shown in FIG. 51described above, the partition parameter may indicate the direction ofsplitting an image block (e.g., from top-right corner to bottom-leftcorner or from top-left corner to bottom-right corner). In step S4002,the process encodes the first partition and the second partition. Instep S4003, the process writes one or more parameters including thepartition parameter into a bit stream, which the decoder side canreceive and decode to obtain the one or more parameters to perform thesame prediction process (as performed on the encoder side) for the firstand second partitions on the decoder side. The one or more parametersincluding the partition parameter may jointly or separately encodevarious pieces of information such as the non-rectangular shape of thefirst partition, the shape of the second partition, the split directionused to split an image block to obtain the first and second partitions,the first motion vector of the first partition, the second motion vectorof the second partition, etc.

FIG. 59 is a flowchart illustrating a method 5000 performed on thedecoder side. In step S5001, the process parses one or more parametersfrom a bitstream, wherein the one or more parameters include a partitionparameter indicative of splitting of an image block into a plurality ofpartitions including a first partition having a non-rectangular shapeand a second partition. The one or more parameters including thepartition parameter parsed out of the bitstream may jointly orseparately encode various pieces of information needed for the decoderside to perform the same prediction process as performed on the encoderside, such as the non-rectangular shape of the first partition, theshape of the second partition, the split direction used to split animage block to obtain the first and second partitions, the first motionvector of the first partition, the second motion vector of the secondpartition, etc. In step S5002, the process 5000 splits the image blockinto the plurality of partitions based on the partition parameter parsedout of the bitstream. In step S5003, the process decodes the firstpartition and the second partition, as split from the image block.

FIG. 60 is a table of sample partition parameters (“the first indexvalue”) and sets of information jointly encoded by the partitionparameters, respectively, similar in nature to the sample tabledescribed above in FIG. 51. In FIG. 60, the partition parameters (“thefirst index values”) range from 0 to 6 and jointly encode: the shape ofthe first and second partitions split from an image block, the directionof splitting an image block into the first and second partitions, thefirst motion vector predicted for the first partition (FIG. 47, stepS1002), and the second motion vector predicted for the second partition(FIG. 47, step S1002). Specifically, the partition parameter 0 encodesthat neither of the first and second partitions has a triangular shape,and thus the split direction information is “N/A”, the first motionvector information is “N/A”, and the second motion vector information is“N/A”.

The partition parameter 1 encodes the first and second partitions aretriangles, the split direction is from top-left corner to bottom-rightcorner, the first motion vector is the “2nd” motion vector listed in thefirst set of motion vector candidates for the first partition, and thesecond motion vector is the “1st” motion vector listed in the second setof motion vector candidates for the second partition. The partitionparameter 2 encodes the first and second partitions are triangles, thesplit direction is from top-right corner to bottom-left corner, thefirst motion vector is the “1st” motion vector listed in the first setof motion vector candidates for the first partition, and the secondmotion vector is the “2nd” motion vector listed in the second set ofmotion vector candidates for the second partition. The partitionparameter 3 encodes the first and second partitions are triangles, thesplit direction is from top-right corner to bottom-left corner, thefirst motion vector is the “2nd” motion vector listed in the first setof motion vector candidates for the first partition, and the secondmotion vector is the “1st” motion vector listed in the second set ofmotion vector candidates for the second partition. The partitionparameter 4 encodes the first and second partitions are triangles, thesplit direction is from top-left corner to bottom-right corner, thefirst motion vector is the “2nd” motion vector listed in the first setof motion vector candidates for the first partition, and the secondmotion vector is the “2nd” motion vector listed in the second set ofmotion vector candidates for the second partition. The partitionparameter 5 encodes the first and second partitions are triangles, thesplit direction is from top-right corner to bottom-left corner, thefirst motion vector is the “2nd” motion vector listed in the first setof motion vector candidates for the first partition, and the secondmotion vector is the “3rd” motion vector listed in the second set ofmotion vector candidates for the second partition. The partitionparameter 6 encodes the first and second partitions are triangles, thesplit direction is from top-left corner to bottom-right corner, thefirst motion vector is the “3rd” motion vector listed in the first setof motion vector candidates for the first partition, and the secondmotion vector is the “1st” motion vector listed in the second set ofmotion vector candidates for the second partition.

According to some implementations, the partition parameters (indexvalues) may be binarized pursuant to a binarization scheme, which isselected depending on a value of at least one or the one or moreparameters. FIG. 52 illustrates a sample binarization scheme ofbinarizing the index values (the partition parameter values).

FIG. 61 is a table of sample combinations of a first parameter and asecond parameter, wherein one of which is a partition parameterindicative of splitting of an image block into a plurality of partitionsincluding a first partition having a non-rectangular shape and a secondpartition. In this example, the partition parameter may be used toindicate splitting of an image block without jointly encoding otherinformation, which is encoded by one or more of the other parameters.

In the first example in FIG. 61, the first parameter is used to indicatean image block size, and the second parameter is used as the partitionparameter (a flag) to indicate that at least one of a plurality ofpartitions split from an image block has a triangular shape. Suchcombination of the first and second parameters may be used to indicate,for example, 1) when the image block size is larger than 64×64, there isno triangular shape partition, or 2) when the ratio of width and heightof an image block is larger than 4 (e.g., 64×4), there is no triangularshape partition.

In the second example of FIG. 61, the first parameter is used toindicate a prediction mode, and the second parameter is used as thepartition parameter (a flag) to indicate that at least one of aplurality of partitions split from an image block has a triangularshape. Such combination of the first and second parameters may be usedto indicate, for example, 1) when an image block is coded in intra mode,there is no triangular partition.

In the third example of FIG. 61, the first parameter is used as thepartition parameter (a flag) to indicate that at least one of aplurality of partitions split from an image block has a triangularshape, and the second parameter is used to indicate a prediction mode.Such combination of the first and second parameters may be used toindicate, for example, 1) when at least one of the plurality ofpartitions split from an image block has a triangular shape, the imageblock must be inter coded.

In the fourth example of FIG. 61, the first parameter indicates themotion vector of a neighboring block, and the second parameter is usedas the partition parameter which indicates the direction of splitting animage block into two triangles. Such combination of the first and secondparameters may be used to indicate, for example, 1) when the motionvector of a neighboring block is a diagonal direction, the direction ofsplitting the image block into two triangles is from top-left corner tobottom-right corner.

In the fifth example of FIG. 61, the first parameter indicates the intraprediction direction of a neighboring block, and the second parameter isused as the partition parameter which indicates the direction ofsplitting an image block into two triangles. Such combination of thefirst and second parameters may be used to indicate, for example, 1)when the intra prediction direction of a neighboring block is aninverse-diagonal direction, the direction of splitting the image blockinto two triangles is from top-right corner to bottom-left corner.

It should be understood that the tables of one or more parametersincluding the partition parameter and what information is jointly orseparately encoded, as shown in FIGS. 51, 60, and 61, are presented asexamples only and numerous other ways of encoding, jointly orseparately, various information as part of the partition syntaxoperation described above are within the scope of the presentdisclosure. For example, the partition parameter may indicate the firstpartition is a triangle, a trapezoid, or a polygon with at least fivesides and angles. The partition parameter may indicate the secondpartition has a non-rectangular shape, such as a triangle, a trapezoid,and a polygon with at least five sides and angles. The partitionparameter may indicate one or more pieces of information about thesplitting, such as the non-rectangular shape of the first partition, theshape of the second partition (which may be non-rectangular orrectangular), the split direction applied to split an image block into aplurality of partitions (e.g., from a top-left corner of the image blockto a bottom-right corner thereof, and from a top-right corner of theimage block to a bottom-left corner thereof). The partition parametermay jointly encode further information such as the first motion vectorof the first partition, the second motion vector of the secondpartition, image block size, prediction mode, the motion vector of aneighboring block, the intra prediction direction of a neighboringblock, etc. Alternatively, any of the further information may beseparately encoded by one or more parameters other than the partitionparameter.

A partition syntax operation, like the process 4000 of FIG. 58, may beperformed by an image encoder, as shown in FIG. 1 for example, whichincludes circuitry and a memory coupled to the circuitry. The circuitry,in operation, performs a partition syntax operation including: splittingan image block into a plurality of partitions including a firstpartition having a non-rectangular shape and a second partition based ona partition parameter indicative of the splitting (FIG. 58, step S4001);encoding the first partition and the second partition (S4002); andwriting one or more parameters including the partition parameter into abitstream (S4003).

According to another embodiment, as shown in FIG. 1, an image encoder isprovided including: a splitter 102 which, in operation, receives andsplits an original picture into blocks; an adder 104 which, inoperation, receives the blocks from the splitter and predictions from aprediction controller 128, and subtracts each prediction from itscorresponding block to output a residual; a transformer 106 which, inoperation, performs a transform on the residuals outputted from theadder 104 to output transform coefficients; a quantizer 108 which, inoperation, quantizes the transform coefficients to generate quantizedtransform coefficients; an entropy encoder 110 which, in operation,encodes the quantized transform coefficients to generate a bitstream;and the prediction controller 128 coupled to an inter predictor 126, anintra predictor 124, and a memory 118, 122, wherein the inter predictor126, in operation, generates a prediction of a current block based on areference block in an encoded reference picture and the intra predictor124, in operation, generates a prediction of a current block based on anencoded reference block in a current picture. The prediction controller128, in operation, splits an image block into a plurality of partitionsincluding a first partition having a non-rectangular shape and a secondpartition based on a partition parameter indicative of the splitting(FIG. 58, step S4001), and encodes the first partition and the secondpartition (step S4002). The entropy encoder 110, in operation, writesone or more parameters including the partition parameter into abitstream (step S4003).

According to another embodiment, an image decoder is provided, as shownin FIG. 41 for example, which includes circuitry and a memory coupled tothe circuitry. The circuitry, in operation, performs a partition syntaxoperation including: parsing one or more parameters from a bitstream,wherein the one or more parameters include a partition parameterindicative of splitting of an image block into a plurality of partitionsincluding a first partition having a non-rectangular shape and a secondpartition (FIG. 59, step S5001); splitting the image block into theplurality of partitions based on the partition parameter (S5002); anddecoding the first partition and the second partition (S5003).

According to a further embodiment, an image decoder as shown in FIG. 41is provided including: an entropy decoder 202 which, in operation,receives and decodes an encoded bitstream to obtain quantized transformcoefficients; an inverse quantizer 204 and transformer 206 which, inoperation, inverse quantizes the quantized transform coefficients toobtain transform coefficients and inverse transform the transformcoefficients to obtain residuals; an adder 208 which, in operation, addsthe residuals outputted from the inverse quantizer 204 and transformer206 and predictions outputted from a prediction controller 220 toreconstruct blocks; and the prediction controller 220 coupled to aninter predictor 218, an intra predictor 216, and a memory 210, 214,wherein the inter predictor 218, in operation, generates a prediction ofa current block based on a reference block in a decoded referencepicture and the intra predictor 216, in operation, generates aprediction of a current block based on an decoded reference block in acurrent picture. The entropy decoder 202, in operation: parses one ormore parameters from a bitstream, wherein the one or more parametersinclude a partition parameter indicative of splitting of an image blockinto a plurality of partitions including a first partition having anon-rectangular shape and a second partition (FIG. 59, step S5001);splits the image block into the plurality of partitions based on thepartition parameter (S5002); and decodes the first partition and thesecond partition (S5003) in cooperation with the prediction controller220 in some implementations.

According to other examples, an inter predictor may perform thefollowing process.

All motion vector candidates included in the first set of motion vectorcandidates may be uni-prediction motion vectors. That is, the interpredictor may determine only uni-prediction motion vectors as motionvector candidates in the first set of motion vector candidates.

The inter predictor may select only uni-prediction motion vectorcandidates from the first set of motion vector candidates.

In an embodiment, only uni-prediction motion vector may be used topredict a small block. The bi-prediction motion vector may be used topredict a big block. As one example, the predicting process may includejudging a size of the image block. When the size of the image block isjudged to be larger than a threshold, the predicting may includeselecting the first motion vector from a first set of motion vectorcandidates, and the first set of motion vector candidates may containuni-prediction and/or bi-prediction motion vectors. When the size of theimage block is judged to be not larger than the threshold, thepredicting may include selecting the first motion vector from a firstset of motion vector candidates, and the first set of motion vectorcandidates may contain only uni-prediction motion vectors.

FIG. 62 is a flow chart illustrating an example of a process flow 6000of predicting a first set of samples for a first partition of a currentpicture with a first motion vector, obtaining a second motion vectorfrom a second partition different from the first partition, predicting asecond set of samples for a first portion included in the firstpartition with the second motion vector, weighting the first and secondsets of samples, storing at least one of the first and second motionvectors for the first partition, and encoding or decoding the firstpartition using the weighted samples, and performing further processingaccording to one embodiment. The process flow 6000 may be performed, forexample, by the encoder 100 of FIG. 1, the decoder 200 of FIG. 41, etc.

In step S6001, a first set of samples for a first partition of a currentpicture is predicted with one or more motion vectors including a firstmotion vector. The first partition may or may not have a non-rectangularshape. The first set of samples may be, for example, pixel blocks havingassociated motion vectors, and luma and chroma pixel components. Forexample, each sample may be a 4 by 4 pixel block associated with thefirst motion vector and having associated luma and chroma pixelcomponents.

The first partition may be, for example, a partition of an image blockwhich has been split into a plurality of partitions. FIG. 63 is aconceptual diagram for illustrating exemplary methods of splitting animage block into a first partition and a second partition. See alsoFIGS. 48, 54 and 55. For example, as shown in FIG. 63, an image blockmay be split into two or more partitions having various shapes. Theexample illustrations of FIG. 63 include: an image block split from atop-left corner of the image block to a bottom-right corner of the imageblock to create a first partition and a second partition both having anon-rectangular shape (e.g., a triangular shape); an image block splitinto an L-shaped partition and a rectangular-shaped partition; an imageblock split into a pentagon-shaped partition and a triangular-shapedpartition; an image block split into a hexagon-shaped partition and apentagon-shaped partition; and an image block slit into twopolygon-shaped partitions. The various illustrated partition shapes maybe formed by splitting an image block in other manners. For example, twotriangular shaped partitions may be formed by splitting an image blockfrom a top-right corner of the image block to a bottom-left corner ofthe image block to create a first partition and a second partition bothhaving a triangular shape. In some embodiments, two or more partitionsof an image block may have an overlapping portion.

In some embodiments, the first motion vector may be obtained using amotion estimation process. In some embodiments, the first motion vectormay be parsed from a bit stream. In some embodiments, the first motionvector may be a motion vector predicted from a set of motion vectorcandidates for at least the first partition. Motion vector candidates ofa motion vector candidate list may include motion vector candidatesderived from spatial or temporal neighboring partitions of the at leasta first partition, or may derive from a motion vector candidate list foran image block for a prediction mode, such as a merge mode, a skip modeor an inter mode.

FIG. 64 is a conceptual diagram for illustrating adjacent andnon-adjacent spatially neighboring partitions of a first partition of acurrent picture. The adjacent spatially neighboring partition is apartition adjacent to the first partition in the current picture. Thenon-adjacent spatially neighboring partition is a partition spaced apartfrom the first partition in the current picture. In some embodiments, aset of motion vector candidates may be derived from the spatiallyneighboring partitions of the at least a first partition in the currentpicture.

The first motion vector may be, for example, a uni-prediction motionvector or a bi-prediction motion vector. FIG. 65 is a conceptual diagramfor illustrating uni-prediction and bi-prediction motion vectorcandidates for an image block of a current picture. A uni-predictionmotion vector candidate is a single motion vector for the current blockin the current picture with respect to a single reference picture. Asillustrated in the top portion of FIG. 65, the uni-prediction motionvector candidate is a motion vector from a block of a current picture toa block of a reference picture, with the reference picture appearingbefore the current picture in a display order. In some embodiments, thereference picture may appear after the current picture in the displayorder.

A bi-prediction motion vector candidate comprises two motion vectors: afirst motion vector for the current block with respect to a firstreference picture and a second motion vector for the current block withrespect to a second reference picture. As illustrated FIG. 65, thebi-prediction motion vector candidate on the bottom left has a firstmotion vector from the block of the current picture to a block of afirst reference picture, and a second motion vector from the block ofthe current picture to a block of a second reference picture. Asillustrated, the first and second reference pictures appear before thecurrent picture in a display order. The bi-prediction motion vectorcandidate on the bottom right of FIG. 65 has a first motion vector fromthe block of the current picture to a block of a first referencepicture, and a second motion vector from the block of the currentpicture to a block of a second reference picture. The first referencepicture appears before the current picture in a display order, and thesecond reference picture appears after the current picture in thedisplay order.

In some embodiments, some partition shapes may be associated with onetype of prediction motion vector. For example, in some embodimentstriangular-shaped partitions may be associated with uni-predictionmotion vector candidates.

The prediction of the first set of samples may include a motioncompensation process with one or more motion vectors including the firstmotion vector, and the motion compensation process may predict samplesfrom a current picture (intra block) or predict samples from a differentpicture (inter block), or combinations thereof.

In step S6002, one or more motion vectors including a second motionvector are obtained from a second partition different from the firstpartition. The second partition may be, for example, a spatially ortemporally co-located partition of the first partition. A portion of thesecond partition may overlap spatially with a portion of the firstpartition. The second motion vector may be obtained using a motionestimation process. In some embodiments, the second motion vector may beparsed from a bit stream. In some embodiments, the second motion vectormay be a motion vector predicted from a set of motion vector candidatesfor at least the second partition. Motion vector candidates of a motionvector candidate list may include motion vector candidates derived fromspatial or temporal neighboring partitions of the second partition, ormay derive from a motion vector candidate list for an image block for aprediction mode, such as a merge mode, a skip mode or other inter modes.The second motion vector may be a uni-prediction motion vector or abi-prediction motion vector.

At step S6003, a second set of samples is predicted for a portion of thefirst partition with one or more motion vectors including the secondmotion vector. The first portion of the first partition is smaller thanthe first partition and positioned adjacent to an edge of the firstpartition, and overlaps the first set of samples. The prediction of thesecond set of samples may include a motion compensation process with oneor more motion vectors including the second motion vector, and themotion compensation process may predict samples from a current picture(intra block) or predict samples from a different picture (inter block),or combinations thereof. The second set of samples may be, for example,pixel blocks having associated motion vectors, and luma and chroma pixelcomponents. For example, each sample of the second set of samples may bea 4 by 4 pixel block associated with the second motion vector and havingassociated luma and chroma pixel components.

FIG. 66 is a conceptual diagram for illustrating examples of the firstportion of the first partition and the first and second sets of samples.The first portion may be, for example, one quarter of the width orheight of the first partition. In another example, the first portion mayhave a width corresponding to N samples adjacent to an edge of the firstpartition, where N is an integer greater than zero, for example, N maybe the integer 2. As illustrated, the right example of FIG. 66 shows arectangular partition having a rectangular portion with a width which isone fourth of the width of the first partition, with the first set ofsamples including samples outside of the first portion and samplesinside of the first portion, and the second set of samples includingsamples within the first portion. The center example of FIG. 66 shows arectangular partition having a rectangular portion with a height whichis one fourth of the height of the first partition, with the first setof samples including samples outside of the first portion and samplesinside of the first portion, and the second set of samples includingsamples within the first portion. The left example of FIG. 66 shows atriangular partition having a polygonal portion with a height whichcorresponds to two samples, with the first set of samples includingsamples outside of the first portion and samples inside of the firstportion, and the second set of samples including samples within thefirst portion.

The first portion may be a portion of the first partition which overlapswith an adjacent partition. FIG. 67 is a conceptual diagram forillustrating a first portion of a first partition, which is a portion ofthe first partition that overlaps with a portion of an adjacentpartition. For ease of illustration, a rectangular partition having anoverlapping portion with a spatially adjacent rectangular partition isshown. Partitions having other shapes, such as triangular partitions,may be employed, and the overlapping portions may overlap with aspatially or temporally adjacent partition. The adjacent partition maybe the second partition.

At step S6004, a weighting process is performed for the first portionincluded in the first partition using a subset of the first set ofsamples included in the first portion and the second set of samplesincluded in the first portion. The weighting may be performed as part ofa boundary smoothing process, such as an overlapped block motioncompensation process (OBMC, see FIGS. 35 and 36 and the descriptionthereof), the boundary smoothing processes described with reference toFIGS. 47-61, etc. For example, pixels from the first set of samples inthe first portion may be assigned various weights, for example, based ona distance of a sample from an edge of the first partition with whichthe first portion is aligned. Samples closer to the edge may be assignedlower weights than the samples farther from the edge. Similarly, pixelsfrom the second set of samples in the first portion of the firstpartition may be assigned various weights, for example, based on adistance of a sample from an edge of the first partition with which thefirst portion is aligned. Samples closer to the edge may be assignedhigher weights than the samples farther from the edge.

In step S6005, one or more motion vectors are stored for the firstportion of the first partition, the stored motion vector(s) being basedon one or both of the first motion vector and the second motion vector.In some embodiments, the stored motion vector(s) may take into accountreference picture lists to which the first and second motion vectorspoint.

For example, FIG. 68 is a conceptual diagram for illustrating an examplecase where the first motion vector and the second motion vector areuni-prediction motion vectors pointing to different pictures indifferent reference picture lists. In some embodiments, when the firstmotion vector and the second motion vector are uni-prediction motionvectors pointing to different pictures in different reference picturelists, the first and second motion vectors may be combined and stored asa bi-prediction motion vector for the first portion of the firstpartition. As illustrated in FIG. 68, the current picture is POC 4. Thefirst motion vector Mv1 is a uni-prediction motion vector pointing toreference picture POC 0 of reference picture list L0, which includesreference pictures POC 0 to POC 8. The second motion vector Mv2 is auni-prediction motion vector pointing to reference picture POC 16 ofreference picture list L1, which includes reference pictures POC 8 toPOC 16. The first motion vector Mv1 and the second motion vector Mv2 arecombined and stored as a bi-prediction motion vector for the firstportion of the first partition.

In another example, FIG. 69 is a conceptual diagram for illustrating anexample case where the first motion vector and the second motion vectorare uni-prediction motion vectors pointing to pictures in a singlereference picture list. A bi-prediction motion vector points to twodifferent reference picture lists. Thus, simply combining the first andsecond motion vectors will not produce a bi-prediction motion vector. Insome embodiments, when the first motion vector and the second motionvector are uni-prediction motion vectors pointing to different referencepictures of a single reference picture list, if one of the referencepictures pointed to is, for example, included in another referencepicture list, the motion vector associated with that picture (forexample, the second motion vector if the reference picture to which itpoints is included in both reference picture lists) may be representedby a motion vector pointing to the same reference picture in the anotherreference picture list. The first and second motion vectors may becombined by replacing the motion vector associated with the referencepicture with a replacement motion vector pointing to the referencepicture in the another reference picture list, and stored as abi-prediction motion vector for the first portion of the firstpartition. As illustrated in FIG. 69, the current picture is POC 4. Thefirst motion vector Mv1 is a uni-prediction motion vector pointing toreference picture POC 0 of reference picture list L0, which includesreference pictures POC 0 to POC 8. The second motion vector Mv2 is auni-prediction motion vector pointing to reference picture POC 8 ofreference picture list L0. Reference picture POC 8 is also included inreference picture list L1. The second motion vector Mv2 is replaced withreplacement motion vector Mv2′, which points to reference picture POC 8in reference picture list L1. The first motion vector Mv1 and thereplacement second motion vector Mv2′ are combined and stored as abi-prediction motion vector for the first portion of the firstpartition. In other words, different lists may be used which point tothe same picture.

In another example, FIG. 70, FIG. 71 and FIG. 72 are conceptual diagramsfor illustrating an example case where the first motion vector and thesecond motion vector are uni-prediction motion vectors pointing to thesame reference picture in the same reference picture list. In someembodiments, when the first motion vector and the second motion vectorare uni-prediction motion vectors pointing to the same reference picturein the same reference picture list, the first motion vector is stored asa uni-prediction motion vector for the first portion of the firstpartition. As illustrated in FIG. 70, the current picture is POC 4. Thefirst motion vector Mv1 is a uni-prediction motion vector pointing toreference picture POC 0 of reference picture list L0, which includesreference pictures POC 0 to POC 8. The second motion vector Mv2 is auni-prediction motion vector pointing to reference picture POC 0 ofreference picture list L0. The first motion vector Mv1 is stored as auni-prediction motion vector for the first portion of the firstpartition.

In some embodiments, when the first motion vector and the second motionvector are uni-prediction motion vectors pointing to the same referencepicture in the same reference picture list, the second motion vector isstored as a uni-prediction motion vector for the first portion of thefirst partition. As illustrated in FIG. 71, the current picture is POC4. The first motion vector Mv1 is a uni-prediction motion vectorpointing to reference picture POC 0 of reference picture list L0, whichincludes reference pictures POC 0 to POC 8. The second motion vector Mv2is a uni-prediction motion vector pointing to reference picture POC 0 ofreference picture list L0. The second motion vector Mv2 is stored as auni-prediction motion vector for the first portion of the firstpartition.

In some embodiments, when the first motion vector and the second motionvector are uni-prediction motion vectors pointing to the same referencepicture in the same reference picture list, the second motion vector isreplaced with a flipped motion vector pointing to a reference picture ofanother reference picture list, and the first motion vector and theflipped motion vector are combined and stored as a bi-prediction motionvector for the first portion of the first partition. As illustrated inFIG. 72, the current picture is POC 4. The first motion vector Mv1 is auni-prediction motion vector pointing to reference picture POC 0 ofreference picture list L0, which includes reference pictures POC 0 toPOC 8. The second motion vector Mv2 is a uni-prediction motion vectorpointing to reference picture POC 0 of reference picture list L0. Thesecond motion vector Mv2 replaced with a flipped motion vector Mv2′pointing to a reference picture in reference picture list L1, asillustrated reference picture POC 8 of reference picture list L1. Thefirst motion vector Mv1 and the flipped motion vector Mv2′ are combinedand stored as a bi-prediction motion vector for the first portion of thefirst partition. The reference picture of the another reference picturelist may be selected in various ways, For example, a reference picturein a same position in reference picture list L1 as the position of thereference picture to which the second motion vector points in referencepicture list L0 may be selected, a reference picture in referencepicture list L1 which is a same distance in display order from thecurrent picture as the distance in display order of the referencepicture to which the second motion vector points in reference picturelist L0 may be selected, etc. The flipped motion vector may be scaled asneeded depending on the reference picture of the another referencepicture list to which the flipped motion vector points.

In some embodiments, a bi-directional prediction vector based on thefirst and second motion vectors is stored for the first portion of thefirst partition when it is possible to do so without flipping or scalingof one of the first and second motion vectors (see, e.g., theembodiments of FIG. 68 and FIG. 69), and a uni-prediction motion vectoris stored for the first portion of the first partition when it is notpossible to generate a bi-prediction motion vector without flipping orscaling of one of the first and second motion vectors (see, e.g., FIGS.70 and 71, where one of the first motion vector or the second motionvector is stored as a uni-prediction motion vector for the first portionof the first partition.

In another example, when the first and the second motion vectors areuni-prediction motion vectors pointing to a same reference picture, thefirst and second motion vectors may be averaged to generate auni-prediction motion vector which is stored as a uni-prediction motionvector for the first portion of the first partition.

In another example, one of the first and the second motion vectors maybe a bi-prediction motion vector, and the other may be a uni-predictionmotion vector. The bi-prediction motion vector may be stored as themotion vector for the first portion of the first partition.

In another example, both of the first and the second motion vectors maybe bi-prediction motion vectors and the reference pictures of the firstmotion vector may be the same as those of the second motion vector. Thefirst and second motion vectors may be averaged to generate abi-prediction motion vector which is stored as a bi-prediction motionvector for the first portion of the first partition.

In another example, both of the first and the second motion vectors maybe bi-prediction motion vectors and the reference pictures of the firstmotion vector may be different from those of the second motion vector.The second motion vector may be scaled to the reference pictures of thefirst motion vector, and averaged with the first motion vector,generating an average bi-prediction motion vector, which may be storedas a bi-prediction motion vector of the first portion of the firstpartition.

In another example, the first motion vector may be stored as the motionvector of the first portion of the first partition, for example, always,or when certain conditions exist. In another example, the second motionvector may be stored as the motion vector of the first portion of thefirst partition, for example, always, or when certain conditions exist.At step S6006, the first partition is encoded or decoded using at leastthe weighted samples of the first portion of the first partition. Forexample, weighted pixel component values (e.g., luma values, chromavalues) of a sample of the first set of samples and weighted pixelcomponent values of a corresponding sample of the second set of samplesmay be combined to determine pixel component values employed in theencoding or decoding process. See, e.g., FIGS. 47-61 and thecorresponding descriptions thereof.

The disclosed embodiments introduce methods of storing a motion vectorof a weighted area (e.g., the first portion of the first partition inthe disclosed examples). This may improve the accuracy of motion vectorprediction for the next coding partition, which may improve theefficiency of the coding. It is noted that motion vectors of a weightedarea may typically be stored for blocks of four pixels. For example,each sample may be a four-by-four pixel block for which a motion vectoris stored. A uni-prediction motion vector or a bi-prediction motionvector for a weighted area may be stored without resulting insignificant, or in any, increase in the amount of memory employed tostore motion vectors for the weighted area.

It is noted that the terms “encoding” and “coding” used in thedescription for the encoding method and the encoding process performedby an image encoding device may be replaced with the term “decoding” fora decoding method and a decoding process performed by an image decodingdevice. All of the described processes and elements are not alwaysneeded, and one or more of the described processes may be omitted insome embodiments.

One or more of the aspects disclosed herein may be performed bycombining at least part of the other aspects in the present disclosure.In addition, one or more of the aspects disclosed herein may beperformed by combining, with other aspects, part of the processesindicated in any of the flow charts according to the aspects, part ofthe configuration of any of the devices, part of syntaxes, etc.

[Implementations and Applications]

As described in each of the above embodiments, each functional oroperational block may typically be realized as an MPU (micro processingunit) and memory, for example. Moreover, processes performed by each ofthe functional blocks may be realized as a program execution unit, suchas a processor which reads and executes software (a program) recorded ona recording medium such as ROM. The software may be distributed. Thesoftware may be recorded on a variety of recording media such assemiconductor memory. Note that each functional block can also berealized as hardware (dedicated circuit). Various combinations ofhardware and software may be employed.

The processing described in each of the embodiments may be realized viaintegrated processing using a single apparatus (system), and,alternatively, may be realized via decentralized processing using aplurality of apparatuses. Moreover, the processor that executes theabove-described program may be a single processor or a plurality ofprocessors. In other words, integrated processing may be performed, and,alternatively, decentralized processing may be performed.

Embodiments of the present disclosure are not limited to the aboveexemplary embodiments; various modifications may be made to theexemplary embodiments, the results of which are also included within thescope of the embodiments of the present disclosure.

Next, application examples of the moving picture encoding method (imageencoding method) and the moving picture decoding method (image decodingmethod) described in each of the above embodiments will be described, aswell as various systems that implement the application examples. Such asystem may be characterized as including an image encoder that employsthe image encoding method, an image decoder that employs the imagedecoding method, or an image encoder-decoder that includes both theimage encoder and the image decoder. Other configurations of such asystem may be modified on a case-by-case basis.

[Usage Examples]

FIG. 73 illustrates an overall configuration of content providing systemex100 suitable for implementing a content distribution service. The areain which the communication service is provided is divided into cells ofdesired sizes, and base stations ex106, ex107, ex108, ex109, and ex110,which are fixed wireless stations in the illustrated example, arelocated in respective cells.

In content providing system ex100, devices including computer ex111,gaming device ex112, camera ex113, home appliance ex114, and smartphoneex115 are connected to internet ex101 via internet service providerex102 or communications network ex104 and base stations ex106 throughex110. Content providing system ex100 may combine and connect anycombination of the above devices. In various implementations, thedevices may be directly or indirectly connected together via a telephonenetwork or near field communication, rather than via base stations ex106through ex110. Further, streaming server ex103 may be connected todevices including computer ex111, gaming device ex112, camera ex113,home appliance ex114, and smartphone ex115 via, for example, internetex101. Streaming server ex103 may also be connected to, for example, aterminal in a hotspot in airplane ex117 via satellite ex116.

Note that instead of base stations ex106 through ex110, wireless accesspoints or hotspots may be used. Streaming server ex103 may be connectedto communications network ex104 directly instead of via internet ex101or internet service provider ex102, and may be connected to airplaneex117 directly instead of via satellite ex116.

Camera ex113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex115 is a smartphone device,cellular phone, or personal handy-phone system (PHS) phone that canoperate under the mobile communications system standards of the 2G, 3G,3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex114 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex103 via, for example, base stationex106. When live streaming, a terminal (e.g., computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, or aterminal in airplane ex117) may perform the encoding processingdescribed in the above embodiments on still-image or video contentcaptured by a user via the terminal, may multiplex video data obtainedvia the encoding and audio data obtained by encoding audio correspondingto the video, and may transmit the obtained data to streaming serverex103. In other words, the terminal functions as the image encoderaccording to one aspect of the present disclosure.

Streaming server ex103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, andterminals inside airplane ex117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed data maydecode and reproduce the received data. In other words, the devices mayeach function as the image decoder, according to one aspect of thepresent disclosure.

[Decentralized Processing]

Streaming server ex103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client may be dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some type oferror or change in connectivity due, for example, to a spike in traffic,it is possible to stream data stably at high speeds, since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers, orswitching the streaming duties to a different edge server and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex113 or the like extracts a feature amount(an amount of features or characteristics) from an image, compressesdata related to the feature amount as metadata, and transmits thecompressed metadata to a server. For example, the server determines thesignificance of an object based on the feature amount and changes thequantization accuracy accordingly to perform compression suitable forthe meaning (or content significance) of the image. Feature amount datais particularly effective in improving the precision and efficiency ofmotion vector prediction during the second compression pass performed bythe server. Moreover, encoding that has a relatively low processingload, such as variable length coding (VLC), may be handled by theterminal, and encoding that has a relatively high processing load, suchas context-adaptive binary arithmetic coding (CABAC), may be handled bythe server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos, and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real time.

Since the videos are of approximately the same scene, management and/orinstructions may be carried out by the server so that the videoscaptured by the terminals can be cross-referenced. Moreover, the servermay receive encoded data from the terminals, change the referencerelationship between items of data, or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Furthermore, the server may stream video data after performingtranscoding to convert the encoding format of the video data. Forexample, the server may convert the encoding format from MPEG to VP(e.g., VP9), may convert H.264 to H.265, etc.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

[3D, Multi-Angle]

There has been an increase in usage of images or videos combined fromimages or videos of different scenes concurrently captured, or of thesame scene captured from different angles, by a plurality of terminalssuch as camera ex113 and/or smartphone ex115. Videos captured by theterminals may be combined based on, for example, the separately obtainedrelative positional relationship between the terminals, or regions in avideo having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture, either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. The server may separately encodethree-dimensional data generated from, for example, a point cloud and,based on a result of recognizing or tracking a person or object usingthree-dimensional data, may select or reconstruct and generate a videoto be transmitted to a reception terminal, from videos captured by aplurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting a video at a selected viewpointfrom three-dimensional data reconstructed from a plurality of images orvideos. Furthermore, as with video, sound may be recorded fromrelatively different angles, and the server may multiplex audio from aspecific angle or space with the corresponding video, and transmit themultiplexed video and audio.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyes,and perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced, so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server may superimpose virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoder may obtain orstore virtual object information and three-dimensional data, generatetwo-dimensional images based on movement from the perspective of theuser, and then generate superimposed data by seamlessly connecting theimages. Alternatively, the decoder may transmit, to the server, motionfrom the perspective of the user in addition to a request for virtualobject information. The server may generate superimposed data based onthree-dimensional data stored in the server in accordance with thereceived motion, and encode and stream the generated superimposed datato the decoder. Note that superimposed data typically includes, inaddition to RGB values, an a value indicating transparency, and theserver sets the a value for sections other than the object generatedfrom three-dimensional data to, for example, 0, and may perform theencoding while those sections are transparent. Alternatively, the servermay set the background to a determined RGB value, such as a chroma key,and generate data in which areas other than the object are set as thebackground. The determined RGB value may be predetermined.

Decoding of similarly streamed data may be performed by the client(e.g., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV. This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area, or inspect a region in further detail upclose.

In situations in which a plurality of wireless connections are possibleover near, mid, and far distances, indoors or outdoors, it may bepossible to seamlessly receive content using a streaming system standardsuch as MPEG-DASH. The user may switch between data in real time whilefreely selecting a decoder or display apparatus including the user'sterminal, displays arranged indoors or outdoors, etc. Moreover, using,for example, information on the position of the user, decoding can beperformed while switching which terminal handles decoding and whichterminal handles the displaying of content. This makes it possible tomap and display information, while the user is on the move in route to adestination, on the wall of a nearby building in which a device capableof displaying content is embedded, or on part of the ground. Moreover,it is also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal, or when encoded data is copied to an edge server in a contentdelivery service.

[Scalable Encoding]

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 74, which is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 74. Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode based on internalfactors, such as the processing ability on the decoder side, andexternal factors, such as communication bandwidth, the decoder side canfreely switch between low resolution content and high resolution contentwhile decoding. For example, in a case in which the user wants tocontinue watching, for example at home on a device such as a TVconnected to the internet, a video that the user had been previouslywatching on smartphone ex115 while on the move, the device can simplydecode the same stream up to a different layer, which reduces the serverside load.

Furthermore, in addition to the configuration described above, in whichscalability is achieved as a result of the pictures being encoded perlayer, with the enhancement layer being above the base layer, theenhancement layer may include metadata based on, for example,statistical information on the image. The decoder side may generate highimage quality content by performing super-resolution imaging on apicture in the base layer based on the metadata. Super-resolutionimaging may improve the SN ratio while maintaining resolution and/orincreasing resolution. Metadata includes information for identifying alinear or a non-linear filter coefficient, as used in super-resolutionprocessing, or information identifying a parameter value in filterprocessing, machine learning, or a least squares method used insuper-resolution processing.

Alternatively, a configuration may be provided in which a picture isdivided into, for example, tiles in accordance with, for example, themeaning of an object in the image. On the decoder side, only a partialregion is decoded by selecting a tile to decode. Further, by storing anattribute of the object (person, car, ball, etc.) and a position of theobject in the video (coordinates in identical images) as metadata, thedecoder side can identify the position of a desired object based on themetadata and determine which tile or tiles include that object. Forexample, as illustrated in FIG. 75, metadata may be stored using a datastorage structure different from pixel data, such as an SEI(supplemental enhancement information) message in HEVC. This metadataindicates, for example, the position, size, or color of the main object.

Metadata may be stored in units of a plurality of pictures, such asstream, sequence, or random access units. The decoder side can obtain,for example, the time at which a specific person appears in the video,and by fitting the time information with picture unit information, canidentify a picture in which the object is present, and can determine theposition of the object in the picture.

[Web Page Optimization]

FIG. 76 illustrates an example of a display screen of a web page oncomputer ex111, for example. FIG. 77 illustrates an example of a displayscreen of a web page on smartphone ex115, for example. As illustrated inFIG. 76 and FIG. 77, a web page may include a plurality of image linksthat are links to image content, and the appearance of the web page maydiffer depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoder) may display, as the image links,still images included in the content or I pictures; may display videosuch as an animated gif using a plurality of still images or I pictures;or may receive only the base layer, and decode and display the video.

When an image link is selected by the user, the display apparatusperforms decoding while, for example, giving the highest priority to thebase layer. Note that if there is information in the HTML code of theweb page indicating that the content is scalable, the display apparatusmay decode up to the enhancement layer. Further, in order to guaranteereal-time reproduction, before a selection is made or when the bandwidthis severely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Still further, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures, and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

[Autonomous Driving]

When transmitting and receiving still image or video data such as two-or three-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., containingthe reception terminal is mobile, the reception terminal may seamlesslyreceive and perform decoding while switching between base stations amongbase stations ex106 through ex110 by transmitting information indicatingthe position of the reception terminal. Moreover, in accordance with theselection made by the user, the situation of the user, and/or thebandwidth of the connection, the reception terminal may dynamicallyselect to what extent the metadata is received, or to what extent themap information, for example, is updated.

In content providing system ex100, the client may receive, decode, andreproduce, in real time, encoded information transmitted by the user.

[Streaming of Individual Content]

In content providing system ex100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, and short content from anindividual are also possible. Such content from individuals is likely tofurther increase in popularity. The server may first perform editingprocessing on the content before the encoding processing, in order torefine the individual content. This may be achieved using the followingconfiguration, for example.

In real time while capturing video or image content, or after thecontent has been captured and accumulated, the server performsrecognition processing based on the raw data or encoded data, such ascapture error processing, scene search processing, meaning analysis,and/or object detection processing. Then, based on the result of therecognition processing, the server—either when prompted orautomatically—edits the content, examples of which include: correctionsuch as focus and/or motion blur correction; removing low-priorityscenes such as scenes that are low in brightness compared to otherpictures, or out of focus; object edge adjustment; and color toneadjustment. The server encodes the edited data based on the result ofthe editing. It is known that excessively long videos tend to receivefewer views. Accordingly, in order to keep the content within a specificlength that scales with the length of the original video, the servermay, in addition to the low-priority scenes described above,automatically clip out scenes with low movement, based on an imageprocessing result. Alternatively, the server may generate and encode avideo digest based on a result of an analysis of the meaning of a scene.

There may be instances in which individual content may include contentthat infringes a copyright, moral right, portrait rights, etc. Suchinstance may lead to an unfavorable situation for the creator, such aswhen content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Further, the server may be configured torecognize the faces of people other than a registered person in imagesto be encoded, and when such faces appear in an image, may apply amosaic filter, for example, to the face of the person. Alternatively, aspre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background to be processed. The server may process the specifiedregion by, for example, replacing the region with a different image, orblurring the region. If the region includes a person, the person may betracked in the moving picture, and the person's head region may bereplaced with another image as the person moves.

Since there is a demand for real-time viewing of content produced byindividuals, which tends to be small in data size, the decoder may firstreceive the base layer as the highest priority, and perform decoding andreproduction, although this may differ depending on bandwidth. When thecontent is reproduced two or more times, such as when the decoderreceives the enhancement layer during decoding and reproduction of thebase layer, and loops the reproduction, the decoder may reproduce a highimage quality video including the enhancement layer. If the stream isencoded using such scalable encoding, the video may be low quality whenin an unselected state or at the start of the video, but it can offer anexperience in which the image quality of the stream progressivelyincreases in an intelligent manner. This is not limited to just scalableencoding; the same experience can be offered by configuring a singlestream from a low quality stream reproduced for the first time and asecond stream encoded using the first stream as a reference.

[Other Implementation and Application Examples]

The encoding and decoding may be performed by LSI (large scaleintegration circuitry) ex500 (see FIG. 73), which is typically includedin each terminal. LSI ex500 may be configured of a single chip or aplurality of chips. Software for encoding and decoding moving picturesmay be integrated into some type of a recording medium (such as aCD-ROM, a flexible disk, or a hard disk) that is readable by, forexample, computer ex111, and the encoding and decoding may be performedusing the software. Furthermore, when smartphone ex115 is equipped witha camera, the video data obtained by the camera may be transmitted. Inthis case, the video data may be coded by LSI ex500 included insmartphone ex115.

Note that LSI ex500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content, or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content, or when the terminalis not capable of executing a specific service, the terminal may firstdownload a codec or application software and then obtain and reproducethe content.

Aside from the example of content providing system ex100 that usesinternet ex101, at least the moving picture encoder (image encoder) orthe moving picture decoder (image decoder) described in the aboveembodiments may be implemented in a digital broadcasting system. Thesame encoding processing and decoding processing may be applied totransmit and receive broadcast radio waves superimposed with multiplexedaudio and video data using, for example, a satellite, even though thisis geared toward multicast, whereas unicast is easier with contentproviding system ex100.

[Hardware Configuration]

FIG. 78 illustrates further details of smartphone ex115 shown in FIG.73. FIG. 79 illustrates a configuration example of smartphone ex115.Smartphone ex115 includes antenna ex450 for transmitting and receivingradio waves to and from base station ex110, camera ex465 capable ofcapturing video and still images, and display ex458 that displaysdecoded data, such as video captured by camera ex465 and video receivedby antenna ex450. Smartphone ex115 further includes user interface ex466such as a touch panel, audio output unit ex457 such as a speaker foroutputting speech or other audio, audio input unit ex456 such as amicrophone for audio input, memory ex467 capable of storing decoded datasuch as captured video or still images, recorded audio, received videoor still images, and mail, as well as decoded data, and slot ex464 whichis an interface for SIM ex468 for authorizing access to a network andvarious data. Note that external memory may be used instead of memoryex467.

Main controller ex460, which may comprehensively control display ex458and user interface ex466, power supply circuit ex461, user interfaceinput controller ex462, video signal processor ex455, camera interfaceex463, display controller ex459, modulator/demodulator ex452,multiplexer/demultiplexer ex453, audio signal processor ex454, slotex464, and memory ex467 are connected via bus ex470.

When the user turns on the power button of power supply circuit ex461,smartphone ex115 is powered on into an operable state, and eachcomponent is supplied with power from a battery pack.

Smartphone ex115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex460, whichincludes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex456 is converted into a digital audiosignal by audio signal processor ex454, to which spread spectrumprocessing is applied by modulator/demodulator ex452 and digital-analogconversion, and frequency conversion processing is applied bytransmitter/receiver ex451, and the resulting signal is transmitted viaantenna ex450. The received data is amplified, frequency converted, andanalog-digital converted, inverse spread spectrum processed bymodulator/demodulator ex452, converted into an analog audio signal byaudio signal processor ex454, and then output from audio output unitex457. In data transmission mode, text, still-image, or video data maybe transmitted under control of main controller ex460 via user interfaceinput controller ex462 based on operation of user interface ex466 of themain body, for example. Similar transmission and reception processing isperformed. In data transmission mode, when sending a video, still image,or video and audio, video signal processor ex455 compression encodes,via the moving picture encoding method described in the aboveembodiments, a video signal stored in memory ex467 or a video signalinput from camera ex465, and transmits the encoded video data tomultiplexer/demultiplexer ex453. Audio signal processor ex454 encodes anaudio signal recorded by audio input unit ex456 while camera ex465 iscapturing a video or still image, and transmits the encoded audio datato multiplexer/demultiplexer ex453. Multiplexer/demultiplexer ex453multiplexes the encoded video data and encoded audio data using adetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex452 andtransmitter/receiver ex451, and transmits the result via antenna ex450.The determined scheme may be predetermined.

When video appended in an email or a chat, or a video linked from a webpage, is received, for example, in order to decode the multiplexed datareceived via antenna ex450, multiplexer/demultiplexer ex453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex455 via synchronous busex470, and supplies the encoded audio data to audio signal processorex454 via synchronous bus ex470. Video signal processor ex455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex458 via display controller ex459. Audio signalprocessor ex454 decodes the audio signal and outputs audio from audiooutput unit ex457. Since real-time streaming is becoming increasinglypopular, there may be instances in which reproduction of the audio maybe socially inappropriate, depending on the user's environment.Accordingly, as an initial value, a configuration in which only videodata is reproduced, i.e., the audio signal is not reproduced, may bepreferable; audio may be synchronized and reproduced only when an input,such as when the user clicks video data, is received.

Although smartphone ex115 was used in the above example, otherimplementations are conceivable: a transceiver terminal including bothan encoder and a decoder; a transmitter terminal including only anencoder; and a receiver terminal including only a decoder. In thedescription of the digital broadcasting system, an example is given inwhich multiplexed data obtained as a result of video data beingmultiplexed with audio data is received or transmitted. The multiplexeddata, however, may be video data multiplexed with data other than audiodata, such as text data related to the video. Further, the video dataitself rather than multiplexed data may be received or transmitted.

Although main controller ex460 including a CPU is described ascontrolling the encoding or decoding processes, various terminals ofteninclude GPUs. Accordingly, a configuration is acceptable in which alarge area is processed at once by making use of the performance abilityof the GPU via memory shared by the CPU and GPU, or memory including anaddress that is managed so as to allow common usage by the CPU and GPU.This makes it possible to shorten encoding time, maintain the real-timenature of the stream, and reduce delay. In particular, processingrelating to motion estimation, deblocking filtering, sample adaptiveoffset (SAO), and transformation/quantization can be effectively carriedout by the GPU instead of the CPU in units of pictures, for example, allat once.

The invention claimed is:
 1. An image encoder comprising: circuitry; anda memory coupled to the circuitry; wherein the circuitry, in operation:predicts a first set of pixels for a first partition of a currentpicture with a first motion vector; predicts a second set of pixels fora second partition with a second motion vector; weights pixels of thefirst set of pixels and the second set of pixels for a first portion inwhich the first partition is overlapped with the second partition;stores for the first portion one of the first motion vector and thesecond motion vector in response to a first condition; stores for thefirst portion both of the first motion vector and the second motionvector in response to a second condition different from the firstcondition; and encodes the first partition using at least the weightedpixels.
 2. The encoder of claim 1, wherein the circuitry, in operation:generates the second motion vector.
 3. The encoder of claim 1, whereinthe first motion vector is a uni-prediction motion vector.
 4. Theencoder of claim 3, wherein the second motion vector is a uni-predictionmotion vector.
 5. The encoder of claim 4, wherein the stored motionvector is a bi-prediction motion vector including the first motionvector and the second motion vector.
 6. The encoder of claim 4, whereinthe stored motion vector is a bi-prediction motion vector including oneof the first and second motion vectors and a replacement vector of theother of the first and second motion vectors.
 7. The encoder of claim 4,wherein the stored motion vector is a bi-prediction motion vectorincluding one of the first and second motion vectors and a flip of theother of the first and second motion vectors.
 8. The encoder of claim 4,wherein the stored motion vector is one of the first motion vector andthe second motion vector.
 9. The encoder of claim 4, wherein the storedmotion vector is a uni-prediction motion vector generated by averagingthe first motion vector and the second motion vector.
 10. The encoder ofclaim 1 wherein the first partition is a triangular shaped partition.11. The encoder of claim 1 wherein the second partition is a triangularshaped partition.
 12. The encoder of claim 10 wherein the secondpartition is a triangular shaped partition.
 13. The encoder of claim 4,wherein the circuitry, in operation: generates the stored motion vectorbased on reference picture lists associated with the first and secondmotion vectors.
 14. The encoder of claim 13, wherein the circuitry, inoperation: determines whether a reference picture list associated withthe first motion vector is associated with the second motion vector; inresponse to a determination that the reference picture list associatedwith the first motion vector is associated with the second motionvector, stores one of the first and second motion vectors as auni-prediction motion vector for the first portion of the firstpartition; and in response to a determination that the reference picturelist associated with the first motion vector is not associated with thesecond motion vector, stores a bi-prediction motion vector including thefirst motion vector and the second motion vector for the first portionof the first partition.
 15. The encoder of claim 13, wherein thecircuitry, in operation: determines whether a reference picture listassociated with the first motion vector is associated with the secondmotion vector; in response to a determination that the reference picturelist associated with the first motion vector is associated with thesecond motion vector, determines whether a reference picture associatedwith one of the first and second motion vectors is included in anotherreference picture list; and in response to a determination that areference picture associated with one of the first motion vector and thesecond motion vector is included in another reference picture list:generates a replacement motion vector for the one of the first andsecond motion vectors, the replacement vector pointing to the referencepicture in the another reference picture list; and stores abi-prediction motion vector including the replacement motion vector andthe other of the first and second motion vectors as the stored motionvector for the first portion of the first partition.
 16. The encoder ofclaim 15, wherein the circuitry, in operation: in response to adetermination that a reference picture associated with the first motionvector and a reference picture associated with the second motion vectorare not included in another reference picture list, stores one of thefirst and the second motion vectors as the stored motion vector for thefirst portion of the first partition.
 17. An image encoder comprising: asplitter which, in operation, receives and splits an original pictureinto blocks, a first adder which, in operation, receives the blocks fromthe splitter and predictions from a prediction controller, and subtractseach prediction from its corresponding block to output a residual, atransformer which, in operation, performs a transform on the residualsoutputted from the adder to output transform coefficients, a quantizerwhich, in operation, quantizes the transform coefficients to generatequantized transform coefficients, an entropy encoder which, inoperation, encodes the quantized transform coefficients to generate abitstream, an inverse quantizer and transformer which, in operation,inverse quantizes the quantized transform coefficients to obtain thetransform coefficients and inverse transforms the transform coefficientsto obtain the residuals, a second adder which, in operation, adds theresiduals outputted from the inverse quantizer and transformer and thepredictions outputted from the prediction controller to reconstruct theblocks, and the prediction controller coupled to an inter predictor, anintra predictor, and a memory, wherein the inter predictor, inoperation, generates a prediction of a current block based on areference block in an encoded reference picture and the intra predictor,in operation, generates a prediction of a current block based on anencoded reference block in a current picture, wherein the interpredictor, in operation, predicts a first set of pixels for a firstpartition of a current picture with a first motion vector; predicts asecond set of pixels for a second partition with a second motion vector;weights pixels of the first set of pixels and the second set of pixelsfor a first portion in which the first partition is overlapped with thesecond partition; stores for the first portion one of the first motionvector and the second motion vector in response to a first condition;stores for the first portion both of the first motion vector and thesecond motion vector in response to a second condition different fromthe first condition; and encodes the first partition using at least theweighted pixels.
 18. The image encoder of claim 17, wherein the interpredictor, in operation: generates the second motion vector.
 19. Theimage encoder of claim 17, wherein the first motion vector is auni-prediction motion vector and the second motion vector is auni-prediction motion vector.
 20. The image encoder of claim 19, whereinthe stored motion vector is a bi-prediction motion vector including thefirst motion vector and the second motion vector.
 21. The image encoderof claim 19, wherein the stored motion vector is a bi-prediction motionvector including one of the first and second motion vectors and areplacement vector of the other of the first and second motion vectors.22. The image encoder of claim 19, wherein the stored motion vector isone of the first motion vector and the second motion vector.
 23. Theimage encoder of claim 19 wherein the first partition is a triangularshaped partition.
 24. The image encoder of claim 19, wherein the interpredictor, in operation: generates the stored motion vector based onreference picture lists associated with the first and second motionvectors.
 25. The image encoder of claim 24, wherein the inter predictor,in operation: determines whether a reference picture list associatedwith the first motion vector is associated with the second motionvector; in response to a determination that the reference picture listassociated with the first motion vector is associated with the secondmotion vector, stores one of the first and second motion vectors as auni-prediction motion vector for the first portion of the firstpartition; and in response to a determination that the reference picturelist associated with the first motion vector is not associated with thesecond motion vector, stores a bi-prediction motion vector including thefirst motion vector and the second motion vector for the first portionof the first partition.
 26. The image encoder of claim 24, wherein theinter predictor, in operation: determines whether a reference picturelist associated with the first motion vector is associated with thesecond motion vector; in response to a determination that the referencepicture list associated with the first motion vector is associated withthe second motion vector, determines whether a reference pictureassociated with one of the first and second motion vectors is includedin another reference picture list; and in response to a determinationthat a reference picture associated with one of the first motion vectorand the second motion vector is included in another reference picturelist: generates a replacement motion vector for the one of the first andsecond motion vectors, the replacement vector pointing to the referencepicture in the another reference picture list; and stores abi-prediction motion vector including the replacement motion vector andthe other of the first and second motion vectors as the stored motionvector for the first portion of the first partition.
 27. The imageencoder of claim 26, wherein the inter predictor, in operation: inresponse to a determination that a reference picture associated with thefirst motion vector and a reference picture associated with the secondmotion vector are not included in another reference picture list, storesone of the first and the second motion vectors as the stored motionvector for the first portion of the first partition.
 28. An imageencoding method, comprising: predicting a first set of pixels for afirst partition of a current picture with a first motion vector;predicting a second set of pixels for a second partition with a secondmotion vector; weighting pixels of the first set of pixels and thesecond set of pixels for a first portion in which the first partition isoverlapped with the second partition; storing for the first portion oneof the first motion vector and the second motion vector in response to afirst condition; storing for the first portion both of the first motionvector and the second motion vector in response to a second conditiondifferent from the first condition; and encoding the first partitionusing at least the weighted pixels.
 29. The image encoding method ofclaim 28, wherein the first motion vector is a uni-prediction motionvector and the second motion vector is a uni-prediction motion vector.30. The image encoding method of claim 29, comprising: generating thestored motion vector based on reference picture lists associated withthe first and second motion vectors.
 31. The image encoding method ofclaim 30, comprising: determining whether a reference picture listassociated with the first motion vector is associated with the secondmotion vector; in response to a determination that the reference picturelist associated with the first motion vector is associated with thesecond motion vector, storing one of the first and second motion vectorsas a uni-prediction motion vector for the first portion of the firstpartition; and in response to a determination that the reference picturelist associated with the first motion vector is not associated with thesecond motion vector, storing a bi-prediction motion vector includingthe first motion vector and the second motion vector for the firstportion of the first partition.
 32. The image encoding method of claim30, comprising: determining whether a reference picture list associatedwith the first motion vector is associated with the second motionvector; in response to a determination that the reference picture listassociated with the first motion vector is associated with the secondmotion vector, determining whether a reference picture associated withone of the first and second motion vectors is included in anotherreference picture list; and in response to a determination that areference picture associated with one of the first motion vector and thesecond motion vector is included in another reference picture list:generating a replacement motion vector for the one of the first andsecond motion vectors, the replacement vector pointing to the referencepicture in the another reference picture list; and storing abi-prediction motion vector including the replacement motion vector andthe other of the first and second motion vectors as the stored motionvector for the first portion of the first partition.
 33. The imageencoding method of claim 32, comprising: in response to a determinationthat a reference picture associated with the first motion vector and areference picture associated with the second motion vector are notincluded in another reference picture list, storing one of the first andthe second motion vectors as the stored motion vector for the firstportion of the first partition.
 34. The image encoding method of claim28, wherein the first motion vector and the second motion vector arestored without being flipped or scaled.
 35. The image encoding method ofclaim 28, wherein one or both of the first motion vector and the secondmotion vector are stored after flipping.
 36. The image encoder of claim1, wherein the first motion vector and the second motion vector arestored without being flipped or scaled.
 37. The image encoder method ofclaim 1, wherein one or both of the first motion vector and the secondmotion vector are stored after flipping.
 38. The image encoder of claim17, wherein the first motion vector and the second motion vector arestored without being flipped or scaled.
 39. The image encoder method ofclaim 17, wherein one or both of the first motion vector and the secondmotion vector are stored after flipping.